{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [],
"source": [
"# NO CODE\n",
"from ch7_forecasting.scripts.cursus import *"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"# Forecasting\n",
"\n",
"## De dataset\n",
"\n",
"Om de technieken duidelijk te maken, zullen we werken met de volgende dataset:\n",
"\n",
"`20, 100, 175, 13, 37, 136, 245, 26, 75, 155, 326, 48, 92, 202, 384, 82, 176, 282, 445, 181`\n",
"\n",
"Dit zijn de **opbrengsten** van een firma voor ieder kwartaal, gedurende de laatste 5 jaar. We kunnen deze data in Python inlezen met:\n",
"\n",
"```python\n",
"opbrengsten = np.array([20,100,175,13,37,\n",
" 136,245,26,75,155,\n",
" 326,48,92, 202,384,\n",
" 82,176,282,445,181], dtype=float)\n",
"\n",
"pd.DataFrame(opbrengsten.reshape(-1, 4),\n",
" columns=['Q{}'.format(i) for i in range(1, 5)],\n",
" index=['Jaar {}'.format(i) for i in range(1, 6)])\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Q1</th>\n",
" <th>Q2</th>\n",
" <th>Q3</th>\n",
" <th>Q4</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Jaar 1</th>\n",
" <td>20</td>\n",
" <td>100</td>\n",
" <td>175</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jaar 2</th>\n",
" <td>37</td>\n",
" <td>136</td>\n",
" <td>245</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jaar 3</th>\n",
" <td>75</td>\n",
" <td>155</td>\n",
" <td>326</td>\n",
" <td>48</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jaar 4</th>\n",
" <td>92</td>\n",
" <td>202</td>\n",
" <td>384</td>\n",
" <td>82</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jaar 5</th>\n",
" <td>176</td>\n",
" <td>282</td>\n",
" <td>445</td>\n",
" <td>181</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Q1 Q2 Q3 Q4\n",
"Jaar 1 20 100 175 13\n",
"Jaar 2 37 136 245 26\n",
"Jaar 3 75 155 326 48\n",
"Jaar 4 92 202 384 82\n",
"Jaar 5 176 282 445 181"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"opbrengsten = np.array([20, 100, 175, 13, 37, 136, 245, 26, 75, 155, 326, 48, 92, 202, 384, 82, 176, 282, 445, 181])\n",
"\n",
"to_kwartalen_df(opbrengsten)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"```{note}\n",
"Voor wie geïnteresseerd is, kunnen we deze gegevens ook m.b.v. volgende code in een grafiek zetten:\n",
"\n",
"```python\n",
"import matplotlib.pyplot as plt\n",
"\n",
"n = opbrengsten.size\n",
"\n",
"fig, ax = plt.subplots(figsize=(10, 5))\n",
"ax.set_title('Opbrengsten voorbije 5 jaar')\n",
"ax.set_xlabel('kwartaal')\n",
"ax.set_ylabel('opbrengst (€)')\n",
"ax2 = ax.secondary_xaxis('top')\n",
"ax2.set_xticks(range(n))\n",
"ax2.set_xticklabels(['Q{}'.format(j % 4 + 1) for j in range(n)])\n",
"\n",
"ax.set_xticks(range(n))\n",
"ax.plot(opbrengsten, label='gegeven', color='C0', marker='o')\n",
"for i in range(0, n, 4):\n",
" ax.axvline(i, color='gray', linewidth=0.5)\n",
"\n",
"ax.legend()\n",
"plt.show()\n",
"```\n",
"```\n",
"Dit resulteert in het volgende:"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"import numpy as np\n",
"from scripts.forecast import *\n",
"\n",
"opbrengsten = np.array([20, 100, 175, 13, 37, 136, 245, 26, 75, 155, 326, 48, 92, 202, 384, 82, 176, 282, 445, 181])\n",
"\n",
"plot_trends(opbrengsten)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Hier zit duidelijk een regelmaat in. De opbrengsten tonen ieder jaar hetzelfde patroon en de opbrengsten stijgen ook met de tijd. In de volgende tekst gaan we een aantal modellen opstellen die proberen om een voorspelling te maken voor de volgende kwartalen. Aangezien sommige modellen beter kunnen voorspellen dan andere, hebben we ook een maat nodig om dat te bepalen. Dit wordt allemaal uitvoerig besproken."
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"## Forecasting op basis van het verleden\n",
"\n",
"In dit deel bespreken we een paar heel eenvoudige technieken om waarden te voorspellen. Ze geven inzicht in de eigenschappen en problematiek van forecasting. Met deze modellen kan je ook tonen hoe je kan inschatten of een model goed of minder goed is (de betrouwbaarheid van de voorspelling). We bespreken volgende voorspellingstechnieken:\n",
"\n",
"* **Naïeve forecasting** (Naive)\n",
"* **Gemiddelde van alle vorige waarden** (Average)\n",
"* **Voortschrijdend gemiddelde** (Moving Average)\n",
"* **Lineaire combinatie** (Linear Combination)\n",
"\n",
"We zullen al deze voorspellingstechnieken onderbrengen in één Pythonscript (`forecast.py`) te samen met enkele functies om hun kwaliteit te beoordelen."
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"### Naïeve forecasting\n",
"\n",
"De eerste vorm van forecasting is heel eenvoudig: we gaan ervan uit dat de laatst gemeten waarde zal blijven. In ons voorbeeld zullen we de grafiek dus aanvullen met de waarde 181 voor de volgende kwartalen. Deze voorspellingsmethode is in de praktijk niet echt zinvol, maar het is wel interessant om een aantal begrippen te tonen. We kunnen deze manier van voorspellen ook iets wiskundiger noteren. Als er $n$ waarden zijn en als we de gegeven waarden $x_{i}$ noemen (waarbij $i$ gaat van 0 tot $n-1$), dan is de voorspelde waarde $f_{n}$ gelijk aan:\n",
"\n",
"$$f_{n}=x_{n-1}$$\n",
"\n",
"In Python kunnen we deze voorspeller definiëren aan de hand van een functie. De input van deze functie is een vector met alle gegevens van het verleden en de output is de eerstvolgende voorspelde waarde (in dit geval de laatste waarde):\n",
"\n",
"```python\n",
"import numpy as np\n",
"\n",
"# voorspelling is vorige waarde\n",
"def naive(y: np.array):\n",
" if y.size > 0:\n",
" return y[-1]\n",
" return np.NaN\n",
"```\n",
"Je kan deze voorspellerfunctie dan toepassen op de gegevens:\n",
"\n",
"```python\n",
"naive(opbrengsten)\n",
"```\n",
"met als resultaat:"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"181.0"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"from scripts.forecast import *\n",
"\n",
"naive(opbrengsten)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"### Meerdere voorspellingen maken\n",
"\n",
"Om de voorspelling verder te laten werken, kan je de voorspelde waarde iedere keer toe en gebruik je de functie weer (we voorspellen hier 4 waarden):\n",
"\n",
"```python\n",
"from scripts.forecast import naive\n",
"\n",
"verleden = opbrengsten\n",
"voorspeld = np.empty()\n",
"\n",
"for i in range(4):\n",
" volgende = naive(verleden)\n",
" voorspeld = np.append(voorspeld, volgende)\n",
" verleden = np.append(verleden, volgende)\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"array([ 20., 100., 175., 13., 37., 136., 245., 26., 75., 155., 326.,\n",
" 48., 92., 202., 384., 82., 176., 282., 445., 181., 181., 181.,\n",
" 181., 181.])"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"verleden = opbrengsten\n",
"voorspeld = np.empty(0)\n",
"\n",
"for i in range(4):\n",
" volgende = naive(verleden)\n",
" voorspeld = np.append(voorspeld, volgende)\n",
" verleden = np.append(verleden, volgende)\n",
"\n",
"verleden"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Zoals verwacht geeft dit iedere keer weer 181 als resultaat. Bovenstaande code werkt dus, maar deze werkwijze is **weinig flexibel**: we moeten telkens apart opgeven welke voorspellerfunctie we willen gebruiken, en het aantal dagen dat we vooruit willen voorspellen. We schrijven daarom eerst een functie `predictor` die een voorspellingen kan maken met eender welke andere voorspellersfunctie (momenteel hebben we alleen nog maar `naive` geschreven).\n",
"\n",
"Deze nieuwe functie werkt als een **Python generator**. Een generator kan je een beetje vergelijken met de Java `Iterator`-interface waarmee je over een collectie van gegevens kunt itereren.\n",
"\n",
"Hieronder zie je een eenvoudige generator die positieve getallen kan genereren.\n",
"\n",
"```python\n",
"# een voorbeeld van een generator\n",
"def generator():\n",
" i = 0\n",
" while True:\n",
" # yield is de output van één aanroep van de generator\n",
" yield i*i\n",
" i += 1\n",
"\n",
"gen = generator() # generator aanmaken\n",
"\n",
"next(gen) # waarden genereren\n",
"next(gen)\n",
"next(gen)\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 5,
"metadata": {},
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{
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"1"
]
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"execution_count": 5,
"metadata": {},
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{
"data": {
"text/plain": [
"4"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"def generator():\n",
" i = 0\n",
" while True:\n",
" yield i * i # yield is de output van één aanroep van de generator\n",
" i += 1\n",
"\n",
"\n",
"gen = generator() # generator aanmaken\n",
"\n",
"next(gen)\n",
"next(gen)\n",
"next(gen)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Je kan de generator ook gebruiken in een for-loop of list comprehension zoals je hieronder ziet:\n",
"```python\n",
"gen = generator()\n",
"[next(gen) for _ in range(10)]\n",
"```\n",
"met als resultaat:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"gen = generator()\n",
"[next(gen) for _ in range(10)]"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Een generator produceert telkens een nieuwe waarde dankzij het `yield` statement.\n",
"\n",
"We gebruiken deze techniek nu om onze predict-generator te schrijven.\n",
"\n",
"```python\n",
"import numpy as np\n",
"# generator functie, y zijn de opbrengsten, forecast de functie\n",
"def predictor(y: np.array, f, *argv):\n",
" i = 0\n",
" while True:\n",
" if i <= y.size: # verleden voorspellen\n",
" yield f(y[:i], *argv) # geef voorspelde waarde terug\n",
" else: # toekomst voorspellen\n",
" y = np.append(y, f(y, *argv)) # plak voorspelling achteraan\n",
" yield f(y, *argv) # geef voorspelde waarde terug\n",
" i += 1\n",
"```\n",
"\n",
"Onze `predict`-generatorfunctie heeft drie argumenten:\n",
" 1. `y`, een Numpy array waarvoor we voorspellingen willen doen,\n",
" 2. `f` de voorspellersfunctie die we willen gebruiken,\n",
" 3. optionele argumenten voor `f` die hier doorgegeven worden als `*argv`.\n",
"\n",
"Zolang index `i` kleiner is dan lengte van `y`, gebruiken we onze functie `f` om een voorspelling te doen op alle elementen van `y` die voor het element met index i liggen (`y[:i]`). Van zodra de index groter wordt en voorbij het einde van onze voorbeeldgegevens gaat, plakken we telkens onze vorige voorspelling achteraan bij onze gegevens, waarop we dan een nieuwe voorspelling doen.\n",
"\n",
"We kunnen hem als volgt gebruiken om voorspellingen te maken voor alle waarden van opbrengsten:\n",
"\n",
"```python\n",
"gen = predictor(opbrengsten, naive)\n",
"predictions = np.array([next(gen) for _ in range(20)])\n",
"predictions\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Q1</th>\n",
" <th>Q2</th>\n",
" <th>Q3</th>\n",
" <th>Q4</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Jaar 1</th>\n",
" <td>NaN</td>\n",
" <td>20.0</td>\n",
" <td>100.0</td>\n",
" <td>175.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jaar 2</th>\n",
" <td>13.0</td>\n",
" <td>37.0</td>\n",
" <td>136.0</td>\n",
" <td>245.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jaar 3</th>\n",
" <td>26.0</td>\n",
" <td>75.0</td>\n",
" <td>155.0</td>\n",
" <td>326.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jaar 4</th>\n",
" <td>48.0</td>\n",
" <td>92.0</td>\n",
" <td>202.0</td>\n",
" <td>384.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jaar 5</th>\n",
" <td>82.0</td>\n",
" <td>176.0</td>\n",
" <td>282.0</td>\n",
" <td>445.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
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"text/plain": [
" Q1 Q2 Q3 Q4\n",
"Jaar 1 NaN 20.0 100.0 175.0\n",
"Jaar 2 13.0 37.0 136.0 245.0\n",
"Jaar 3 26.0 75.0 155.0 326.0\n",
"Jaar 4 48.0 92.0 202.0 384.0\n",
"Jaar 5 82.0 176.0 282.0 445.0"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"from scripts.forecast import predictor\n",
"\n",
"gen = predictor(opbrengsten, naive)\n",
"predictions = np.array([next(gen) for _ in range(20)])\n",
"to_kwartalen_df(predictions)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Omdat het niet handig is om steeds te werken met een list comprehension schrijven we nog een extra functie die de code hierboven uitvoert. We noemen deze functie `predict`.\n",
"\n",
"```python\n",
"import numpy as np\n",
"\n",
"def predict(y: np.array, start, end, f, *argv):\n",
" # generator aanmaken\n",
" generator = predictor(y, f, *argv)\n",
" # voorspellingen doen\n",
" predictions = np.array([next(generator) for _ in range(end)])\n",
" # opkuisen\n",
" predictions[:start] = np.nan\n",
" return predictions\n",
"```\n",
"Deze functie maakt een generator aan op basis van de gegevens `y` en de voorspellersfunctie `f`. Dan worden er voorspellingen gemaakt waarbij de enkel de delen tussen start en einde behouden blijven. De rest wordt op een NA-waarde gezet, zodat deze niet geplot zullen worden.\n",
"\n",
"Het is handiger om de voorspellingen te vergelijken met de originele waarden. Dit kunnen we door ze te samen te bekijken in een DataFrame.\n",
"```python\n",
"import pandas as pd\n",
"\n",
"df = pd.concat([\n",
" pd.Series(opbrengsten, name='opbrengsten'),\n",
" pd.Series(predictions, name='naive')], axis=1)\n",
"df.index=range(1,21)\n",
"df.transpose()\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
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"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>3</th>\n",
" <th>4</th>\n",
" <th>5</th>\n",
" <th>6</th>\n",
" <th>7</th>\n",
" <th>8</th>\n",
" <th>9</th>\n",
" <th>10</th>\n",
" <th>11</th>\n",
" <th>12</th>\n",
" <th>13</th>\n",
" <th>14</th>\n",
" <th>15</th>\n",
" <th>16</th>\n",
" <th>17</th>\n",
" <th>18</th>\n",
" <th>19</th>\n",
" <th>20</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>opbrengsten</th>\n",
" <td>20.0</td>\n",
" <td>100.0</td>\n",
" <td>175.0</td>\n",
" <td>13.0</td>\n",
" <td>37.0</td>\n",
" <td>136.0</td>\n",
" <td>245.0</td>\n",
" <td>26.0</td>\n",
" <td>75.0</td>\n",
" <td>155.0</td>\n",
" <td>326.0</td>\n",
" <td>48.0</td>\n",
" <td>92.0</td>\n",
" <td>202.0</td>\n",
" <td>384.0</td>\n",
" <td>82.0</td>\n",
" <td>176.0</td>\n",
" <td>282.0</td>\n",
" <td>445.0</td>\n",
" <td>181.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>naive</th>\n",
" <td>NaN</td>\n",
" <td>20.0</td>\n",
" <td>100.0</td>\n",
" <td>175.0</td>\n",
" <td>13.0</td>\n",
" <td>37.0</td>\n",
" <td>136.0</td>\n",
" <td>245.0</td>\n",
" <td>26.0</td>\n",
" <td>75.0</td>\n",
" <td>155.0</td>\n",
" <td>326.0</td>\n",
" <td>48.0</td>\n",
" <td>92.0</td>\n",
" <td>202.0</td>\n",
" <td>384.0</td>\n",
" <td>82.0</td>\n",
" <td>176.0</td>\n",
" <td>282.0</td>\n",
" <td>445.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 1 2 3 4 5 6 7 8 9 \\\n",
"opbrengsten 20.0 100.0 175.0 13.0 37.0 136.0 245.0 26.0 75.0 \n",
"naive NaN 20.0 100.0 175.0 13.0 37.0 136.0 245.0 26.0 \n",
"\n",
" 10 11 12 13 14 15 16 17 18 \\\n",
"opbrengsten 155.0 326.0 48.0 92.0 202.0 384.0 82.0 176.0 282.0 \n",
"naive 75.0 155.0 326.0 48.0 92.0 202.0 384.0 82.0 176.0 \n",
"\n",
" 19 20 \n",
"opbrengsten 445.0 181.0 \n",
"naive 282.0 445.0 "
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"df = pd.concat([\n",
" pd.Series(opbrengsten, name='opbrengsten'),\n",
" pd.Series(predictions, name='naive')], axis=1)\n",
"df.index = range(1, 21)\n",
"df.transpose()"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Naive forecasting kan uiteraard geen voorspelling doen voor het _allereerste_ kwartaal, maar vanaf het tweede kwartaal zie je duidelijk dat de voorspelling gelijk is aan de vorige waarden.\n",
"\n",
"Nog beter is om deze voorspellingen tonen in een grafiek (één beeld zegt meer dan blabla):"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"plot_trends(opbrengsten, predict(opbrengsten, 0, 20, naive), sub_title='Voorspellen met naive forecasting')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Dankzij onze predict functie kunnen we ook heel eenvoudig in de toekomst voorspellen foor de range te vergroten naar bv. 24.\n",
"\n",
"```python\n",
"predictions = predict(opbrengsten, 0, 24, naive)\n",
" ```"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"plot_trends(opbrengsten, predict(opbrengsten, 0, 24, naive),\n",
" sub_title='Enkel toekomst voorspellen met naive forecasting')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Wil je enkel de voorspellingen voor het volgende jaar (4 kwartalen) dan kan dat met deze code:\n",
"\n",
"```python\n",
"predictions = predict(opbrengsten, 20, 24, naive)\n",
"```\n",
"\n",
"Die je ook grafisch kan voorstellen natuurlijk"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"plot_trends(opbrengsten, predict(opbrengsten, 20, 24, naive),\n",
" sub_title='Enkel toekomst voorspellen met Naive Forecasting')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Dit model is op korte termijn misschien wel een redelijke voorspeller, maar op lange termijn zal het alleen maar erger worden, want de waarde blijft constant. Dit is een eigenschap voor alle voorspellingsmethodes: hoe verder je in de toekomst voorspelt, hoe groter de verwachte fout. Je zou dus een soort betrouwbaarheidsinterval kunnen opstellen dat steeds groter wordt, naarmate de tijd vordert. In dit document zullen we daar echter niet verder op in gaan.\n",
"\n",
"### Gemiddelde van alle vorige waarden\n",
"\n",
"De vorige voorspellingsmethode werkt niet goed omdat er niet echt diep in het verleden wordt gekeken. Dit kunnen we oplossen door het gemiddelde te nemen van alle voorgaande metingen en dat als voorspelling te gebruiken. Zo is de voorspelling gebaseerd op het volledige verleden.\n",
"\n",
"Dit wil dus zeggen dat:\n",
"\n",
"\n",
"$$f_{n}=\\frac{1}{n}\\sum_{i=0}^{n-1}x_{i}$$\n",
"\n",
"In Python kan je weer een functie maken:\n",
"\n",
"```python\n",
"# voorspelling is gemiddelde van alle vorige waarden\n",
"import numpy as np\n",
"def average(y: np.array):\n",
" if y.size < 1:\n",
" return np.NaN\n",
" return y.mean()\n",
"```\n",
"\n",
"Als we deze functie gebruiken om opeenvolgende voorspellingen te bekomen, krijgen we steeds de waarde 160 terug.\n",
"\n",
"```python\n",
"predictions = predict(opbrengsten, 20, 24, average)\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"array([ nan, 20. , 60. , 98.33333333,\n",
" 77. , 69. , 80.16666667, 103.71428571,\n",
" 94. , 91.88888889, 98.2 , 118.90909091,\n",
" 113. , 111.38461538, 117.85714286, 135.6 ,\n",
" 132.25 , 134.82352941, 143. , 158.89473684,\n",
" 160. , 160. , 160. , 160. ])"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"predict(opbrengsten, 0, 24, average)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Grafisch levert dit:"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"plot_trends(opbrengsten, predict(opbrengsten, 0, 24, average), sub_title='Toekomst voorspellen met Average Forecasting')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"### Voortschrijdend gemiddelde\n",
"\n",
"Het nadeel van de vorige methode is dat deze steeds de gehele geschiedenis meeneemt in de voorspelling. Als er recent grote wijzigingen zijn gebeurd, dan zal de voorspelling minder goed zijn. We kunnen dit veranderen door steeds het gemiddelde te nemen van de laatste $m$ metingen. Men noemt dit het voortschrijdend gemiddelde. Er geldt dus:\n",
"\n",
"$$f_{n}=\\frac{1}{m}\\sum_{i=n-m}^{n-1}x_{i}$$\n",
"\n",
"In Python kan je dit implementeren met een functie die een extra parameter $m$ krijgt. We kunnen ook pas een voorspelling doen als er minstens $m$ waarden zijn.\n",
"\n",
"```python\n",
"# voorspelling is voortschrijdend gemiddelde van m vorige waarden\n",
"import numpy as np\n",
"\n",
"def moving_average(y: np.array, m=4):\n",
" if y.size < m:\n",
" return np.NaN\n",
"\n",
" return np.mean(y[-m:])\n",
"```\n",
"\n",
"Merk op dat deze voorspellende functie een extra parameter `m` heeft die standaard steeds op `4` staat. Als je hem dus vergeet mee te geven is `m=4`. Herinner je het `*argv` argument van onze generator? Die `*argv` is een 'verzamelbak' voor al extra argumenten die je aan een functie meegeeft. Voor bovenstaande functie zou hij dus de `m` bevatten.\n",
"\n",
"Als we nu de komende 4 kwartalen willen voorspellen met onze predict functie\n",
"\n",
"```python\n",
"predict(opbrengsten, 0, 24, moving_average)\n",
"```\n",
"krijgen we (met `m=4`) de volgende waarden:"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"array([ nan, nan, nan, nan, 77. ,\n",
" 81.25 , 90.25 , 107.75 , 111. , 120.5 ,\n",
" 125.25 , 145.5 , 151. , 155.25 , 167. ,\n",
" 181.5 , 190. , 211. , 231. , 246.25 ,\n",
" 271. , 294.75 , 297.9375 , 261.171875])"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"predict(opbrengsten, 0, 24, moving_average)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Grafisch ziet dit er als volgt uit:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"plot_trends(opbrengsten, predict(opbrengsten, 0, 24, moving_average),\n",
" sub_title='Toekomst voorspellen met Moving Average Forecasting (m=4)')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Merk op dat we ook andere waarden voor $m$ kunnen nemen. Hieronder zie je enkele voorbeelden. Wat is de invloed van de $m$?\n",
"\n",
"```python\n",
"predict(opbrengsten, 0, 24, moving_average, 3) # m = 3\n",
"predict(opbrengsten, 0, 24, moving_average, 6) # m = 6\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"plot_trends(opbrengsten, predict(opbrengsten, 0, 24, moving_average, 3),\n",
" sub_title='Toekomst voorspellen met Moving Average Forecasting (m=3)')\n",
"\n",
"plot_trends(opbrengsten, predict(opbrengsten, 0, 24, moving_average, 6),\n",
" sub_title='Toekomst voorspellen met Moving Average Forecasting (m=6)')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"### Lineaire combinatie\n",
"\n",
"We kunnen de vorige techniek nog verbeteren door een gewogen gemiddelde te berekenen in plaats van een rekenkundig gemiddelde. We gaan de volgende waarde dus voorspellen door gewichten te geven aan de vorige waarden. Deze gewichten schatten we aan de hand van het verleden. Om een voorspelling te maken, moeten we de gewichten vermenigvuldigen met de\n",
"laatste $m$ waarden en dan alles optellen. Men noemt dit een lineaire combinatie van de laatste $m$ waarden. Lineaire combinaties worden heel veel gebruikt in machine learning technieken en zullen dus regelmatig terugkomen in deze cursus.\n",
"\n",
"Er geldt nu:\n",
"\n",
"$$f_{n}=\\sum_{i=n-m}^{n-1}a_{i-n+m}\\cdot x_{i}$$\n",
"\n",
"Als $m=4$, dan kunnen we dit ook schrijven als:\n",
"\n",
"$$f_{n}=a_{0}\\cdot x_{n-4}+a_{1}\\cdot x_{n-3}+a_{2}\\cdot x_{n-2}+a_{3} \\cdot x_{n-1}$$\n",
"\n",
"We kunnen de $a_{i}$ (de gewichten) berekenen uit het verleden. Dat kan op verschillende manieren. De meest eenvoudige manier leert de gewichten uit de $2\\cdot m$ gegevens die voorafgaan aan degene die men wil gebruiken. Als je voor die gegevens de bovenstaande formule uitschrijft, krijg je een stelsel van $m$ vergelijkingen met $m$ onbekenden en dat kan je oplossen."
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"We gaan niet te diep in op de wiskunde van deze techniek, maar geven hier de code in Python om de gewichten te berekenen:\n",
"```python\n",
"# voorspelling is een lineaire combinatie\n",
"import numpy as np\n",
"\n",
"def bereken_gewichten(y: np.array, m: int):\n",
" # n is aantal elementen\n",
" n = y.size\n",
" # we hebben > 2 * m elementen nodig\n",
" if n < 2 * m:\n",
" return np.NaN\n",
" # selecteer de laatste elementen\n",
" M = y[-(m + 1):-1]\n",
" # maak een matrix M van coëfficiënten\n",
" for i in range(1, m):\n",
" M = np.vstack([M, y[-(m + i + 1):-(i + 1)]])\n",
"\n",
" # selecteer de bekenden\n",
" v = np.flip(y[-m:])\n",
" # los het stelsel van m vergelijkingen op\n",
" return np.linalg.solve(M, v)\n",
"\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Wanneer we deze functie gebruiken, vinden we in ons geval volgende gewichten:\n",
"\n",
"```python\n",
"a = bereken_gewichten(y=opbrengsten, m=4)\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"array([1.0080186 , 0.13742887, 0.12600184, 0.08679208])"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"a = bereken_gewichten(opbrengsten, 4)\n",
"a"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"En deze kunnen we nu gebruiken om handmatig een voorspelling te maken volgens bovenstaande formule.\n",
"\n",
"```python\n",
"m = 4\n",
"n = opbrengsten.size\n",
"prediction = (opbrengsten[n-m:n] * a).sum()\n",
"prediction\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"287.94640003946205"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"m = 4\n",
"n = opbrengsten.size\n",
"prediction = (opbrengsten[n - m:n] * a).sum()\n",
"prediction"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"In plaats van dit steeds handmatig te moeten doen, kunnen we dit nu weer samenvatten in een nieuwe voorspellerfunctie:\n",
"\n",
"```python\n",
"import numpy as np\n",
"\n",
"def linear_combination(y: np.array, m=4):\n",
" n = y.size\n",
" # check op minstens 2*m gegevens\n",
" if n < 2 * m:\n",
" return np.NaN\n",
" # bereken de gewichten\n",
" a = bereken_gewichten(y, m)\n",
" # bereken de voorspelde waarde en geef de voorspelde waarde terug\n",
" return np.sum(y[-m:] * a)\n",
"```\n",
"\n",
"Je kan deze functie als volgt gebruiken om waarden te voorspellen:\n",
"\n",
"```python\n",
"prediction = linear_combination(opbrengsten)\n",
"prediction\n",
"```\n",
"met hetzelfde resultaat als tevoren natuurlijk:"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"287.94640003946205"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"from scripts.forecast import linear_combination\n",
"\n",
"linear_combination(opbrengsten)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Als je 4 opeenvolgende waarden voorspelt door gebruik te maken van de generator\n",
"\n",
"```python\n",
"predict(opbrengsten, 0, 24, linear_combination) # m = 3\n",
"```\n",
"dan vind je deze waarden:"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"array([ nan, nan, nan, nan,\n",
" nan, nan, nan, nan,\n",
" 64.37375462, 185.06661482, 347.74993101, 39.00416917,\n",
" 135.71642907, 172.45094295, 433.52852524, 76.26132534,\n",
" 115.46692155, 262.29756407, 462.91536762, 139.89145584,\n",
" 287.94640004, 393.214892 , 543.85261675, 318.7714138 ])"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"predict(opbrengsten, 0, 24, linear_combination) # m = 3"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Merk op dat we 8 waarden moeten wachten alvorens we een eerste voorspelling kunnen doen. Waarom 8?\n",
"\n",
"Grafisch ziet dit er als volgt uit:"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"plot_trends(opbrengsten, predict(opbrengsten, 0, 24, linear_combination),\n",
" sub_title='Toekomst voorspellen met Linear Combination Forecasting (m=4)')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Dit lijkt een hele goede voorspeller, maar hebben we een tikkeltje vals gespeeld door `m=4`. Vier is namelijk duidelijk de periode waarin de herhaling zich voordoet. Wat gebeurt als we een andere waarde kiezen (m=5)?"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"plot_trends(opbrengsten, predict(opbrengsten, 0, 24, linear_combination, 5),\n",
" sub_title='Toekomst voorspellen met Linear Combination Forecasting (m=5)')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Dat ziet er al minder fraai uit. Voor waarden lager dan 4 is de situatie nog slechter. Voor 8 valt het dan weer beter mee...\n",
"\n",
"Een algemeen probleem is dat we momenteel nog niet weten hoe goed elke voorspeller is. We kunnen er geen waarde op plakken. Vandaar dat we dat probleem nu eerst gaan aanpakken in de volgende paragraaf.\n",
"\n",
"## Betrouwbaarheid van een model\n",
"\n",
"Alvorens verder te gaan met andere voorspellingsmethoden, willen we eerst kunnen meten hoe goed een model kan voorspellen. Maar dan hebben we data uit de toekomst nodig en die hebben we niet. Een oplossing bestaat erin om het model toe te passen op eerdere gegevens en kijken hoe goed het de vorige gegevens had kunnen voorspellen. Zo kunnen we de betrouwbaarheid van het model inschatten.\n",
"\n",
"Dat is exact wat we gaan doen. We nemen opeenvolgende kwartalen en laten dit model steeds de toekomst voorspellen. We kijken naar het verschil tussen de voorspelde waarde en de echte waarde. De originele waarden duiden we weer aan met $x_{i}$.\n",
"\n",
"De voorspelde waarden noemen we, naar analogie met voorgaande, $f_{i}$.\n",
"\n",
"Voor naïeve forecasting krijgen we dus: $f_{i}=x_{i-1}$, maar $f_{0}$ bestaat niet omdat er geen $x_{-1}$ is. Vanaf $f_{1}$ kunnen we de waarden uitrekenen.\n",
"\n",
"In Python kunnen we deze waarden ook uitrekenen met onze eerder geschreven generator. Met de generator functie kunnen we nu dus alle voorspellingsfuncties los laten op het verleden met volgende code. We verzamelen ook alles in één dataframe."
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>opbrengsten</th>\n",
" <th>naive</th>\n",
" <th>average</th>\n",
" <th>moving_average</th>\n",
" <th>linear_combination</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>f0</th>\n",
" <td>20.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f1</th>\n",
" <td>100.0</td>\n",
" <td>20.0</td>\n",
" <td>20.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f2</th>\n",
" <td>175.0</td>\n",
" <td>100.0</td>\n",
" <td>60.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f3</th>\n",
" <td>13.0</td>\n",
" <td>175.0</td>\n",
" <td>98.333333</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f4</th>\n",
" <td>37.0</td>\n",
" <td>13.0</td>\n",
" <td>77.000000</td>\n",
" <td>77.00</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f5</th>\n",
" <td>136.0</td>\n",
" <td>37.0</td>\n",
" <td>69.000000</td>\n",
" <td>81.25</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f6</th>\n",
" <td>245.0</td>\n",
" <td>136.0</td>\n",
" <td>80.166667</td>\n",
" <td>90.25</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f7</th>\n",
" <td>26.0</td>\n",
" <td>245.0</td>\n",
" <td>103.714286</td>\n",
" <td>107.75</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f8</th>\n",
" <td>75.0</td>\n",
" <td>26.0</td>\n",
" <td>94.000000</td>\n",
" <td>111.00</td>\n",
" <td>64.373755</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f9</th>\n",
" <td>155.0</td>\n",
" <td>75.0</td>\n",
" <td>91.888889</td>\n",
" <td>120.50</td>\n",
" <td>185.066615</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f10</th>\n",
" <td>326.0</td>\n",
" <td>155.0</td>\n",
" <td>98.200000</td>\n",
" <td>125.25</td>\n",
" <td>347.749931</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f11</th>\n",
" <td>48.0</td>\n",
" <td>326.0</td>\n",
" <td>118.909091</td>\n",
" <td>145.50</td>\n",
" <td>39.004169</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f12</th>\n",
" <td>92.0</td>\n",
" <td>48.0</td>\n",
" <td>113.000000</td>\n",
" <td>151.00</td>\n",
" <td>135.716429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f13</th>\n",
" <td>202.0</td>\n",
" <td>92.0</td>\n",
" <td>111.384615</td>\n",
" <td>155.25</td>\n",
" <td>172.450943</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f14</th>\n",
" <td>384.0</td>\n",
" <td>202.0</td>\n",
" <td>117.857143</td>\n",
" <td>167.00</td>\n",
" <td>433.528525</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f15</th>\n",
" <td>82.0</td>\n",
" <td>384.0</td>\n",
" <td>135.600000</td>\n",
" <td>181.50</td>\n",
" <td>76.261325</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f16</th>\n",
" <td>176.0</td>\n",
" <td>82.0</td>\n",
" <td>132.250000</td>\n",
" <td>190.00</td>\n",
" <td>115.466922</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f17</th>\n",
" <td>282.0</td>\n",
" <td>176.0</td>\n",
" <td>134.823529</td>\n",
" <td>211.00</td>\n",
" <td>262.297564</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f18</th>\n",
" <td>445.0</td>\n",
" <td>282.0</td>\n",
" <td>143.000000</td>\n",
" <td>231.00</td>\n",
" <td>462.915368</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f19</th>\n",
" <td>181.0</td>\n",
" <td>445.0</td>\n",
" <td>158.894737</td>\n",
" <td>246.25</td>\n",
" <td>139.891456</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" opbrengsten naive average moving_average linear_combination\n",
"f0 20.0 NaN NaN NaN NaN\n",
"f1 100.0 20.0 20.000000 NaN NaN\n",
"f2 175.0 100.0 60.000000 NaN NaN\n",
"f3 13.0 175.0 98.333333 NaN NaN\n",
"f4 37.0 13.0 77.000000 77.00 NaN\n",
"f5 136.0 37.0 69.000000 81.25 NaN\n",
"f6 245.0 136.0 80.166667 90.25 NaN\n",
"f7 26.0 245.0 103.714286 107.75 NaN\n",
"f8 75.0 26.0 94.000000 111.00 64.373755\n",
"f9 155.0 75.0 91.888889 120.50 185.066615\n",
"f10 326.0 155.0 98.200000 125.25 347.749931\n",
"f11 48.0 326.0 118.909091 145.50 39.004169\n",
"f12 92.0 48.0 113.000000 151.00 135.716429\n",
"f13 202.0 92.0 111.384615 155.25 172.450943\n",
"f14 384.0 202.0 117.857143 167.00 433.528525\n",
"f15 82.0 384.0 135.600000 181.50 76.261325\n",
"f16 176.0 82.0 132.250000 190.00 115.466922\n",
"f17 282.0 176.0 134.823529 211.00 262.297564\n",
"f18 445.0 282.0 143.000000 231.00 462.915368\n",
"f19 181.0 445.0 158.894737 246.25 139.891456"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 864x504 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"import pandas as pd\n",
"\n",
"n = 21\n",
"y = pd.Series(opbrengsten, name='opbrengsten')\n",
"a = pd.Series(predict(opbrengsten, 0, 20, naive), name='naive')\n",
"b = pd.Series(predict(opbrengsten, 0, 20, average), name='average')\n",
"c = pd.Series(predict(opbrengsten, 0, 20, moving_average), name='moving_average')\n",
"d = pd.Series(predict(opbrengsten, 0, 20, linear_combination), name='linear_combination')\n",
"\n",
"predictions = pd.concat([y, a, b, c, d], axis=1)\n",
"predictions.index = ['f{}'.format(i) for i in range(20)]\n",
"predictions\n",
"ax = predictions.plot(figsize=(12, 7), marker='o')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"De blauwe lijn zijn de originele waarden, en voor naïve forecasting (oranje) is die het origineel maar 1 plaats opgeschoven (de eerste voorspelling bestaat niet omdat er nog geen verleden was). De andere voorspellingsfuncties zijn ook afgebeeld. De lineaire combinatie is zelfs zo goed dat ze op het einde overlapt met de originele opbrengsten.\n",
"\n",
"Als we voor elke voorspellingsfunctie de voorspelde waarde aftrekken van de echte waarde, krijgen we de fout. Deze noteren we met $e_{i}$.\n",
"\n",
"Er geldt dus dat fout voor de i-de voorspelling van een voorspellingsfunctie gelijk is aan:\n",
"\n",
"$$e_{i}=x_{i}-f_{i}$$\n",
"\n",
"De fouten voor alle voorspellingsfuncties en voor alle tijdstippen is dus gelijk aan volgende tabel:"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>naive</th>\n",
" <th>average</th>\n",
" <th>moving_average</th>\n",
" <th>linear_combination</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>f0</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f1</th>\n",
" <td>-80.0</td>\n",
" <td>-80.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f2</th>\n",
" <td>-75.0</td>\n",
" <td>-115.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f3</th>\n",
" <td>162.0</td>\n",
" <td>85.333333</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f4</th>\n",
" <td>-24.0</td>\n",
" <td>40.000000</td>\n",
" <td>40.00</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f5</th>\n",
" <td>-99.0</td>\n",
" <td>-67.000000</td>\n",
" <td>-54.75</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f6</th>\n",
" <td>-109.0</td>\n",
" <td>-164.833333</td>\n",
" <td>-154.75</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f7</th>\n",
" <td>219.0</td>\n",
" <td>77.714286</td>\n",
" <td>81.75</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f8</th>\n",
" <td>-49.0</td>\n",
" <td>19.000000</td>\n",
" <td>36.00</td>\n",
" <td>-10.626245</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f9</th>\n",
" <td>-80.0</td>\n",
" <td>-63.111111</td>\n",
" <td>-34.50</td>\n",
" <td>30.066615</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f10</th>\n",
" <td>-171.0</td>\n",
" <td>-227.800000</td>\n",
" <td>-200.75</td>\n",
" <td>21.749931</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f11</th>\n",
" <td>278.0</td>\n",
" <td>70.909091</td>\n",
" <td>97.50</td>\n",
" <td>-8.995831</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f12</th>\n",
" <td>-44.0</td>\n",
" <td>21.000000</td>\n",
" <td>59.00</td>\n",
" <td>43.716429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f13</th>\n",
" <td>-110.0</td>\n",
" <td>-90.615385</td>\n",
" <td>-46.75</td>\n",
" <td>-29.549057</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f14</th>\n",
" <td>-182.0</td>\n",
" <td>-266.142857</td>\n",
" <td>-217.00</td>\n",
" <td>49.528525</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f15</th>\n",
" <td>302.0</td>\n",
" <td>53.600000</td>\n",
" <td>99.50</td>\n",
" <td>-5.738675</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f16</th>\n",
" <td>-94.0</td>\n",
" <td>-43.750000</td>\n",
" <td>14.00</td>\n",
" <td>-60.533078</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f17</th>\n",
" <td>-106.0</td>\n",
" <td>-147.176471</td>\n",
" <td>-71.00</td>\n",
" <td>-19.702436</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f18</th>\n",
" <td>-163.0</td>\n",
" <td>-302.000000</td>\n",
" <td>-214.00</td>\n",
" <td>17.915368</td>\n",
" </tr>\n",
" <tr>\n",
" <th>f19</th>\n",
" <td>264.0</td>\n",
" <td>-22.105263</td>\n",
" <td>65.25</td>\n",
" <td>-41.108544</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" naive average moving_average linear_combination\n",
"f0 NaN NaN NaN NaN\n",
"f1 -80.0 -80.000000 NaN NaN\n",
"f2 -75.0 -115.000000 NaN NaN\n",
"f3 162.0 85.333333 NaN NaN\n",
"f4 -24.0 40.000000 40.00 NaN\n",
"f5 -99.0 -67.000000 -54.75 NaN\n",
"f6 -109.0 -164.833333 -154.75 NaN\n",
"f7 219.0 77.714286 81.75 NaN\n",
"f8 -49.0 19.000000 36.00 -10.626245\n",
"f9 -80.0 -63.111111 -34.50 30.066615\n",
"f10 -171.0 -227.800000 -200.75 21.749931\n",
"f11 278.0 70.909091 97.50 -8.995831\n",
"f12 -44.0 21.000000 59.00 43.716429\n",
"f13 -110.0 -90.615385 -46.75 -29.549057\n",
"f14 -182.0 -266.142857 -217.00 49.528525\n",
"f15 302.0 53.600000 99.50 -5.738675\n",
"f16 -94.0 -43.750000 14.00 -60.533078\n",
"f17 -106.0 -147.176471 -71.00 -19.702436\n",
"f18 -163.0 -302.000000 -214.00 17.915368\n",
"f19 264.0 -22.105263 65.25 -41.108544"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"predictions.drop(columns='opbrengsten').sub(predictions.opbrengsten, axis=0)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Als ons model de toekomst perfect voorspelt, dan zijn alle $e_{i}=0$. Als het model minder goed is, dan worden de waarden van $e_{i}$ groter (of kleiner als ze negatief zijn). Je kan uit bovenstaande tabel dus al meteen een intuïtief idee krijgen van welke model het beste zal zijn door de te kijken naar de grootte van de fouten.\n",
"\n",
"We kunnen nu de gemiddelde fout proberen te berekenen. Dat is dan een maat voor de betrouwbaarheid van onze voorspeller, maar we kunnen dit niet doen door zomaar een gewoon gemiddelde te nemen, want de sommige $e_i$ zijn negatief. Dit gemiddelde kan je op verschillende andere manieren berekenen waarbij de $e_i$ telkens positief gemaakt worden:\n",
"\n",
"- de **MAE** (Mean Absolute Error) = $\\dfrac{1}{n}{\\displaystyle \\sum_{i=0}^{n-1}}\\left|e_{i}\\right|$\n",
"- de **RMSE** (Root Mean Squared Error) = $\\sqrt{\\dfrac{1}{n}{\\displaystyle \\sum_{i=0}^{n-1}}e_{i}^{2}}$\n",
"- de **MAPE** (Mean Absolute Percentage Error) = $\\dfrac{1}{n}{\\displaystyle {\\displaystyle \\sum_\n",
" {i=0}^{n-1}}}\\left|\\dfrac{e_{i}}{x_{i}}\\right|$\n",
"\n",
"Bemerk dat de formule voor RMSE enorm lijkt op de formule voor standaardafwijking en ook op de formule voor standaardschattingsfout (zie regressie). Het is een veelgebruikte formule om een gemiddelde fout te berekenen. De waarden van MAE en RMSE zijn echter moeilijk te interpreteren. Dat komt omdat de fout bij heel grote waarden ook heel\n",
"groot kan worden. We zijn dus meer geïnteresseerd in de fout *ten opzichte van* de oorspronkelijke data. Vandaar dat\n",
"de MAPE dikwijls gebruikt wordt, maar het nadeel van deze maat is dat de waarden $x_{i}$ niet 0 mogen worden. Als dit het geval is, kan je dus toch enkel maar de MAE en RMSE berekenen.\n",
"\n",
"In Python kunnen we deze fouten als volgt berekenen op basis van de originele waarde $x$ en de voorspellingen $f$.\n",
"\n",
"```python\n",
"import numpy as np\n",
"\n",
"# x en f zijn Numpy arrays\n",
"# x is origineel, f is voorspelling\n",
"e = x - f\n",
"\n",
"# nanmean is gemiddelde zonder NA-waarde\n",
"mae = np.nanmean(np.abs(e))\n",
"# ** 2 is tweede macht\n",
"rmse = np.sqrt(np.nanmean(e ** 2))\n",
"\n",
"mape = np.nanmean(np.abs(e / x))\n",
"```\n",
"\n",
"Enkele voorbeelden\n",
"\n",
"```python\n",
"x = opbrengsten\n",
"f = predict(opbrengsten, 0, 20, naive)\n",
"\n",
"e = x -f\n",
"mae = np.nanmean(np.abs(e))\n",
"rmse = np.sqrt(np.nanmean(e ** 2))\n",
"mape = np.nanmean(np.abs(e / x))\n",
"```\n",
"\n",
"Dit geeft de volgende resultaten voor Naïeve Forecasting:"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"MAE = 137.42105263157896 \n",
"RMSE = 158.6978260720669 \n",
"MAPE = 2.0702566894377608\n"
]
}
],
"source": [
"# NO CODE\n",
"x = opbrengsten\n",
"f = predict(opbrengsten, 0, 20, naive)\n",
"\n",
"e = x - f\n",
"mae = np.nanmean(np.abs(e)) # nanmean is gemiddelde zonder NA-waarde\n",
"rmse = np.sqrt(np.nanmean(e ** 2)) # ** 2 is tweede macht\n",
"mape = np.nanmean(np.abs(e / x))\n",
"\n",
"print('MAE =', mae, '\\nRMSE =', rmse, '\\nMAPE =', mape)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Als je naar de MAPE kijkt, zie je dat de voorspelling gemiddeld dus 207% afwijkt van de echte waarde. Dit is dus niet zo'n goede voorspeller ... (maar dat wisten we intuïtief al).\n",
"\n",
"We maken een functie die al deze grootheden kan berekenen. Dat zou er als volgt uit kunnen zien:\n",
"\n",
"```python\n",
"import numpy as np\n",
"\n",
"def forecast_errors(x: np.array, f: np.array, method: str):\n",
" e = x - f\n",
" mae = np.nanmean(np.abs(e))\n",
" rmse = np.sqrt(np.nanmean(e ** 2))\n",
" mape = np.nanmean(np.abs(e / x))\n",
" return pd.DataFrame({'MAE': [mae], 'RMSE': [rmse], 'MAPE': [mape]}, index=[method])\n",
"```\n",
"\n",
"Je gebruikt deze functie als volgt (bijvoorbeeld voor het voortschrijdend gemiddelde):\n",
"\n",
"```python\n",
"x = opbrengsten\n",
"f = predict(opbrengsten, 0, 20, moving_average)\n",
"\n",
"forecast_errors(x, f, 'moving average')\n",
"```\n",
"met als resultaat:"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>MAE</th>\n",
" <th>RMSE</th>\n",
" <th>MAPE</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>moving average</th>\n",
" <td>92.90625</td>\n",
" <td>113.321342</td>\n",
" <td>0.77707</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" MAE RMSE MAPE\n",
"moving average 92.90625 113.321342 0.77707"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"from scripts.forecast import forecast_errors\n",
"\n",
"x = opbrengsten\n",
"f = predict(opbrengsten, 0, 20, moving_average)\n",
"\n",
"forecast_errors(x, f, 'moving average')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Als je alles goed hebt geïmplementeerd, zou je volgende waarden moeten vinden:"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>MAE</th>\n",
" <th>RMSE</th>\n",
" <th>MAPE</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>naive</th>\n",
" <td>137.421053</td>\n",
" <td>158.697826</td>\n",
" <td>2.070257</td>\n",
" </tr>\n",
" <tr>\n",
" <th>average</th>\n",
" <td>103.004796</td>\n",
" <td>130.806207</td>\n",
" <td>1.036220</td>\n",
" </tr>\n",
" <tr>\n",
" <th>moving average</th>\n",
" <td>92.906250</td>\n",
" <td>113.321342</td>\n",
" <td>0.777070</td>\n",
" </tr>\n",
" <tr>\n",
" <th>linear combination</th>\n",
" <td>28.269228</td>\n",
" <td>32.792905</td>\n",
" <td>0.174283</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" MAE RMSE MAPE\n",
"naive 137.421053 158.697826 2.070257\n",
"average 103.004796 130.806207 1.036220\n",
"moving average 92.906250 113.321342 0.777070\n",
"linear combination 28.269228 32.792905 0.174283"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"x = opbrengsten\n",
"f1 = predict(opbrengsten, 0, 20, naive)\n",
"f2 = predict(opbrengsten, 0, 20, average)\n",
"f3 = predict(opbrengsten, 0, 20, moving_average)\n",
"f4 = predict(opbrengsten, 0, 20, linear_combination)\n",
"pd.concat([forecast_errors(x, f1, 'naive'),\n",
" forecast_errors(x, f2, 'average'),\n",
" forecast_errors(x, f3, 'moving average'),\n",
" forecast_errors(x, f4, 'linear combination')\n",
" ])"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"De lineaire combinatie geeft dus in dit geval het beste resultaat (zoals we grafisch al konden zien). De voorspelde\n",
"waarde wijkt gemiddeld ongeveer 17% af van de echte waarde.\n",
"\n",
"## Een model maken voor de data\n",
"\n",
"Bij de vorige voorspellingsmethodes, probeerden we de volgende waarde te voorspellen aan de hand van het verleden. Maar dat kan ook anders. Je kan ook een model opstellen dat de wetmatigheden in de data beschrijft. Je kan dit model dan gebruiken om voorspellingen te doen, maar ook om het verleden te modelleren. Je zoekt dus een formule of functievoorschrift die het gedrag van de data weergeeft. Het voordeel van een model is dat het ook kan uitleggen waarom de data zich op een bepaalde manier gedraagt. We zien hier 3 technieken:\n",
"\n",
"- trend forecasting,\n",
"- seasonal forecasting en\n",
"- seasonal trend forecasting.\n",
"\n",
"### Trend forecasting\n",
"\n",
"De eenvoudigste manier om een model op te stellen, is door een lijn te zoeken die door de data gaat. Dit kunnen we doen met regressie. Dit kan lineaire regressie zijn, maar natuurlijk ook niet-lineaire regressie. Het model dat uit de regressie komt, is eigenlijk ook een voorspeller. We gaan ervan uit dat onze data een functie is van de tijd en daarom zetten we de nummers $0 \\ldots (n-1)$ in de X-as. Die symboliseren het tijdstip.\n",
"\n",
"In Python gaan we dus geen functie meer maken die de \"volgende waarde\" berekent. In plaats daarvan maken we een functie die een functie als return-value geeft (het model). Die laatste functie kan je gebruiken om te voorspellen. Voor lineaire regressie kunnen we bijvoorbeeld volgende functie maken (we maken gebruik van de functie general_regression() uit het deel over regressie):\n",
"\n",
"```python\n",
"# trend model\n",
"import numpy as np\n",
"from scripts.forecast import GeneralRegression\n",
"\n",
"def create_trend_model(y):\n",
" # we bouwen een lineaire regressie model\n",
" X = np.arange(0, y.size)\n",
" model = GeneralRegression()\n",
" model.fit(X, y)\n",
"\n",
" # we geven een voorspellersfunctie terug\n",
" return lambda x: model.predict([[x]])\n",
"```\n",
"\n",
"Je kan deze functie als volgt gebruiken:\n",
"\n",
"```python\n",
"predict_trend = create_trend_model(opbrengsten)\n",
"predict_trend(20)\n",
"```\n",
"met als resultaat"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"array([282.32105263])"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"predict_trend = create_trend_model(opbrengsten)\n",
"predict_trend(20)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"We kunnen dit ook handmatig doen (zie leerstof Samenhang). In ons voorbeeld vinden dan we volgende formule voor de regressielijn:\n",
"\n",
"$$f_{i}=49.3286+11.6496\\cdot i$$\n",
"\n",
"Als we dus een voorspelling willen doen voor het eerstvolgende kwartaal ($i=20$), dan vinden we:\n",
"\n",
"$$49.3286 + 11.6496 \\cdot 20 = 282.3206$$\n",
"\n",
"Wanneer we dit model zowel in het verleden als de toekomst gebruiken, krijgen we grafisch dit:"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"image/png": 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lqZRSSikVYLqoXymllFIqwDQgU0oppZQKMA3IlFJKKaUCTAOyAYjIjcHUri/b1na1XW1X29V2Q6tdX7at7Q6NBmQD89V/kC//44Otz9qutqvtarvabmDa9WXb2u4QaECmlFJKKRVgQZ32IjIy0kRERPj0OWw2Gw6Hw+vtdnd3Ex4e7vV2fdm2r9oNtmscbO3q9fVtu3p9fduuXl/ftgt6jX3drqe2tja7MSayt/t8+8w+NnfuXDZt2uTT51i7di3Lli3z6XOMdXqNfUuvr2/p9fUtvb6+p9fYf0Tko77u0ylLpZRSSqkA04BMKaWUUirANCBTSimllAqwoF5DppRSSqmRs9vtVFZW0tHREeiuhITo6GgyMzMZysZDDciUUkqpMa6yspKEhARyc3MRkUB3J6gZY6itraWyspK8vLxBP06nLJVSSqkxrqOjg9TUVA3GvEBESE1NHfJoowZkSimllNJgzIuGcy11ylIppZQaoVUFVaxcU0x1QzuTk2JYsTyfyxZkBLpbKohoQKaUUkqNwKqCKm5/ZivtdivbfVVDO7c/sxVAgzI1aBqQKaWUUiOwck3x4WDMrd3uYOWa4pANyHRE0Pt0DZlSSik1AtUN7UM6HuzcI4JVDe0YjowIriqoGnHbP//5z8nPz+fUU0/l6quv5ne/+x179uzhvPPOY9GiRZx22mns2LEDgD179nDiiScyZ84c7rjjDuLj4w+3s3LlSpYsWcLcuXP56U9/CsBtt93G3/72t8Pn3Hnnnfzud7/r8/zS0lJmzZrFV7/6VWbPns25555Le7vv/k91hEwppZQagclJMVT1EnxNTooJQG9G7mfPf8wn1U193l9Q3kCXw3nUsXa7gx889RGPbSjv9THHTR7HTy+e3e/zbty4kaeffpqioiLsdjsLFy5k0aJF3Hjjjdxzzz1Mnz6dDz/8kG984xu8+eab3HLLLdxyyy1cffXV3HPPPYfbefXVV9m1axcbNmzAGMMll1zC22+/zVVXXcWtt97KN7/5TQCefPJJ1qxZ0+f52dnZ7Nq1i8cee4x//etffPazn+Xpp5/m2muvHeylHBINyJRSSqkRWLE8/6g1ZAAxETZWLM8PYK98p2cwNtDxwXrvvfe49NJLiY6OJjo6mosvvpiOjg7ef/99rrzyysPndXZ2AvDBBx+watUqAK655hq+//3vA1ZA9uqrr7JgwQIAWlpa2LVrFzfccAMHDhygurqagwcPkpycTFZWFnfffXev52dnZ5OXl8f8+fMBWLRoEaWlpSP6GfujAZlSSik1ApctyKCpw85PVn8MWMHYry+fE7RrqgYayTrlN2/2OiKYkRTDE187yat9cTqdJCUlUVhYOOjHGGO4/fbb+drXvnbMfVdeeSVPPfUUNTU1XHXVVf2eX1paSlRU1OHvbTabT6csdQ2ZUkopNUITEqwP7uTYCKZNiA/aYGwwVizPJybCdtQxb4wInnLKKTz//PN0dHTQ0tLCCy+8QGxsLHl5efzvf/8DrOCpqKgIgBNPPJGnn34agMcff/xwO8uXL+f++++npaUFgKqqKg4cOADAVVddxeOPP85TTz11eNStv/P9SQMypZRSaoQ2lNQTFR7GecdPovRQK8aYQHfJZy5bkMGvL59DRlIMgjUy5o0RwSVLlnDJJZcwd+5czj//fObMmUNiYiKPPPII9913H/PmzWP27NmsXr0agD/96U/84Q9/YO7cuezevZvExEQAzj33XK655hpOOukk5syZwxVXXEFzczMAs2fPprm5mYyMDCZNmjTg+f6kU5ZKKaXUCG0qq2NeVhL5E+N5rLObQy1djE+IGviBQeqyBRk+GQX8/ve/z5133klbWxunn346ixYtIi8vj1deeeWYczMyMli/fj0iwuOPP05xcfHh+9wL/nuzdevWY471df62bduO6psvaUCmlFJKjUBrZzcfVzdx0xlTyU2LA6C0tjWkAzJfufHGG/nkk0/o6Ojgi1/8IgsXLuzz3M2bN3PzzTdjjCEpKYn777/fjz31Pg3IlFJKqREoKG/A4TQszk0mzxWQlRxqZUluSoB7FnweffTRQZ972mmnHV5PFgo0IFNKKaVGYENpHWECi3KSiYmwEWETSg61BrpbKshoQKaUUkqNwKbSOmZNGkdCdAQAWSmxlGpApoZId1kqpZRSw2R3OCkobzhqejIvNU5HyNSQaUCmlFJKDdO2qkba7Y6jA7K0OEprW3E6Qzf1hfI+DciUUkqpYdpUWg/Aktzkw8dy0+LosDvZ39wRqG4pL3rwwQe5+eabe73Ps6D5SGlAppRSSg3ThtI6clJjmTAu+vCxKe6dlgdDfNqyuQYeOB+a9we6J8fo7u4OdBeGTAMypZRSahiMMWwqrWNxztHpLdy5yEpqQzwgW3cXlK+Hdb8dcVO33XYbf/vb3w5/f+edd7Jy5UpWrFjB8ccfz5w5c3jiiScA67r3dnzt2rWcdtppXHLJJRx33HG0trZy4YUXMm/ePI4//vjD5+Xm5vKDH/yAOXPmsHTpUnbv3g3AwYMH+cxnPsOSJUtYsmQJ77333jH9LCkpOZzR/4477hjxz+1Jd1kqpZRSw7DnYAv1bXaW5iUfdTx9XDRR4WHBO0L28m1Qc2w2+6N0d0H1JjBO2PyAdb4tsu/z0+fA+b/p8+6rrrqKW2+9lW9+85sAPPnkk/zwhz/k1VdfpaioiEOHDrFkyRJOP/103n//fQoLC485DrBlyxa2bdtGXl4eTz/9NJMnT+bFF18EoLGx8fDzJSYmsnXrVh566CFuvfVWXnjhBW655Ra+853vcOqpp1JeXs7y5cvZvn37Uf285ZZbuOmmm/jCF75wVADpDTpCppRSSg3DxsPrx44eIQsLk8ML+0NWYzm463UaAw3lI2puwYIFHDhwgOrqaoqKikhOTqawsJCrr74am83GxIkTOeOMM9i4cSPvvvtur8cBli5dSl5eHgBz5szhtdde44c//CHvvPPO4VqXAFdfffXhfz/44AMAXn/9dW6++Wbmz5/PJZdcQlNT0+GC427vvffe4cded911I/qZe9IRMqWUUmoYNpbUkRYfeTg7v6fc1Dh2HfB/gWqv6GckC7DWjt09D3DvIjXQ0QBX3A8JE4f9tFdeeSVPPfUUNTU1XHXVVZSUlAy5jbi4I/8XM2bMYMuWLbz00kvccccdnH322fzkJz8BQEQOn+e+7XQ6Wb9+PdHR0fTH87HepCNkSiml1DBsLLPWj/X2AZ03Po7yuja6Hc4A9MzH1t1lTVV6Ms4RryW76qqrePzxx3nqqae48sorOe2003jiiSdwOBwcPHiQt99+m6VLl/Z5vKfq6mpiY2O59tprWbFiBVu2bDl8n3s92RNPPMFJJ50EwLnnnstf/vKXw+cUFhYe0+Ypp5zC448/DsAjjzwyop+3Jx0hU0oppYaoprGDirp2vnhSbq/356XGYXcYqhs6yE6N9W/nfK1yAzi6jj7m6LKOj8Ds2bNpbm4mIyODSZMm8elPf5oPPviAefPmISLcddddpKen93l8x44dR7W3detWVqxYQVhYGBEREfzjH/84fF99fT1z584lKiqKxx57DIA///nPfPOb32Tu3Ll0d3dz+umnc8899xzV5t13380111zDb3/7Wy699NIR/bw9iTHBm7hu8eLFZtOmTT59jrVr17Js2TKfPsdYp9fYt/T6+pZeX98ardf3uaJqvv1YAc/dfApzM5OOuX9DSR2f/ecHPHj9EpblT/B/B4dg7dq1TJw4kVmzZgW6K36Rm5vLpk2bSEtL8+nzbN++/ZhrKiKbjTGLeztfpyyVUkqpIdpUWkdspI3jJo3r9X73ujKtaakGy+cBmYjYRKRARF5wfZ8nIh+KyG4ReUJEIl3Ho1zf73bdn+vrvimllFLDsaGkjoXZyYTbev8YTYuPJD4qnNLaNj/3TA2ktLTU56Njw+GPEbJbAM9EHr8F/miMmQbUAze4jt8A1LuO/9F1nlJKKTWqNLbbKd7ffEy6C08iVuqLvUE0QhbMS5hGm+FcS58GZCKSCVwI/Nv1vQBnAU+5TvkPcJnr9qWu73Hdf7b4am+pUkopNUxbyuox5uj6lb3JTYsLminL6OhoamtrNSjzAmMMtbW1A6bP6MnXuyz/BPwASHB9nwo0GGPcRaYqgQzX7QygAsAY0y0ija7zD3k2KCI3AjcCZGdn+7LvSiml1DE2ltYRHibMz07q97y81Fhe/Kiarm4nkeGje8l2ZmYmlZWVHDx4MNBdCQnR0dFkZmYO6TE+C8hE5CLggDFms4gs81a7xph7gXvB2mXprXaVUkqpwdhYWsfsjERiI/v/CM0bH4fTQHldG9MmxPupd8MTERFxOMO9CgxfhuynAJeISCnwONZU5d1Akoi4X8WZQJXrdhWQBeC6PxGo9WH/lFJKqSHpsDsoqmhk6QDTlWBl6wfdaakGx2cBmTHmdmNMpjEmF/gc8KYx5vPAW8AVrtO+CKx23X7O9T2u+980OpmtlFJqFNla1UiXw8nifhb0u7lTX5RoQKYGIRCT2j8Evisiu7HWiN3nOn4fkOo6/l3gtgD0TSmllOrThpI6ABbnDDxClhQbSXJsBCWhXGRceY1fSicZY9YCa1239wLHFJ0yxnQAV/qjP0oppdRwbCqtY+r4OFLjowZ1fjDttFSBpbUslVJqDFhVUMXKNcVUN7QzOSmGFcvzuWxBxsAPVIc5nIZNZfVcNHfSoB+TlxbHB3t0ObQa2Ojeh6uUUmrEVhVUcfszW6lqaMcAVQ3t3P7MVlYVVA34WHXEzv3NNHd095sQtqe81Dj2NXbQ3uXwYc9UKNCATCmlQtzKNcW0248OCNrtDlauKQ5Qj4LTxlJr/dhQArJcd01LXUemBqABmVJKhbjqhvYhHVe921haT/q4aDKTYwb9GC0yrgZLAzKllApxk5N6DyD6Oq6OZYxhY0kdi3OTGUpVP/cIme60VAPRgEwppULciuX5REcc/es+JsLGiuX5AepR8Kmsb6emqYOleYOfrgSIjwpnQkIUJQc1IFP904BMKaVC3GULMvjKqUfK4iTFRPDry+foLsshcK8fW5wztIAMXKkvdIRMDUADMqWUGgMSoiMAEIHrTsrRYGyINpbWkRAdTn56wpAfm5cap9n61YA0IFNKqTGgqLKBrJQYJifGUFHXFujuBJ2NpfUszknGFjb49WNueePjONTSRXOH3Qc9U6FCAzKllBoDiioamZeZRFZKDJX1urtyKOpau9h9oGVQ9St7c6TIuAbCqm8akCmlVIg70NxBVUM787OSyEqOpaJeA4Oh2ORaPzbUBf1uU8ZbAdneQy1e65MKPVo6SSmlQlxRRSMA87OSaO10sL+pkw67g+gIW4B7Fhw2ltYRaQtjTkbisB6fnRKLiI6Qqf7pCJlSSoW4oooGbGHC7MmJZKVYuceqNCnsoG0srWdeVuKwA9joCBuTE2Mo0REy1Q8NyJRSKsQVVTaQPzGBmEgbWSmxALqObJDaurrZVtU47PVjbnlpcZTU6giZ6psGZEopFcKcTkNhRQPzs5MADpf90Z2Wg1NY0UC307B0hAFZblosJQdbMMZ4qWcq1GhAppRSIayktpXmjm7mZyYBMDEhmkhbmC7sH6SNJfWIwMKc5BG1k5saR1NHN/VtmvpC9U4DMqWUCmFFFQ0AzMtKAiAsTMhI1tQXg7WxtI78iQkkxkSMqB33TktNEKv6ogGZUkqFsKKKBuIibUybEH/4WGZyDJU6ZTmgboeTLeX1w0534cmdi0wDMtUXDciUUiqEFVY0MCcz8agM85nJsVToCNmAPtnXRFuXY8QL+gGyUmKxhQmlGpCpPmhAppRSIaqz28En+5oOT1e6ZaXEUNfaRWtnd2A6FiQ2ltYDsCR3ZOvHACJsYWQlx1CiRcZVHzQgU0qpELV9XzN2hzm8oN8tK1lTXwzGxpI6MpNjmJQY45X2ctPiKDmoAZnqnQZkSikVonou6HfT1BcDM8awqaxuxOkuPOWlxVFa26qpL1SvNCBTSqkQVVTRwISEKCYlRh91/EhyWA3I+lJyqJVDLV0s8cKCfre8tDjauhwcbO70WpsqdGhAppRSIaqwooF5WUmIyFHHU+MiiYmw6cL+fmzy4voxt7w0d5FxnbZUx9KATCmlQlBjm529h1qZ32O6EkBEyEyO0SnLfmworSM5NoKp4+MHPnmQ3KkvdKel6o0GZEopFYI+qmoAYF6PBf1uWSmxuqi/HxtL61icm3LM6OJITE6KIdIWprnIVK80IFNKqRDkXtA/Nyux1/uzkmO0fFIfDjR1UFbb5tUF/QC2MCEnNVYDMtUrDciUUioEFVY0MHV8HOOiey/5k5kcS3NHN41aW/EY7vxji724fswt17XTUqmeNCBTSqkQY4yhsKLxmHQXnrJSXKkvdJTsGBtL64iOCOP4jN5HF0diSlocpbVtOJ2a+kIdTQMypZQKMdWNHRxq6ex1Qb9bZrKmvujLxtI6FmQlE2Hz/kdkblocXd1Oqht1/Z46mgZkSikVYtzrx/oLyNzZ+ivqNDDw1NxhZ/u+Jq/mH/OkRcZVXzQgU0qpEFNY0UCkLYyZ6eP6PCcxNoKE6HCdsuxhS3kDToPXF/S7TRmvqS9U7zQgU0qpEFNY0cBxk8cRGd7/r/isZE190dOm0jpsYcKC7CSftD8hIYrYSBslhzQQVkcLD3QHlFIKYFVBFSvXFFPd0M7kpBhWLM/nsgUZge5W0Ol2ONla2chVS7IGPDczOUanznrYUFLH7MnjiIvyzcejiJCTGkfJoRaftK+Cl46QKaUCblVBFbc/s5WqhnYMUNXQzu3PbGVVQVWguxZ0dh9sod3uYF4f+cc8uZPDarFrS2e3g8KKBhbn+Ga60s2901IpTxqQKaUCbuWaYtrtjqOOtdsdrFxTHKAeBa/C8gYA5mcNnEMrKzmGdruD2tYuH/cqOGyraqKz28nSPO/nH/OUmxZLeV0bdofTp8+jgosGZEqpgKtu6H0dU1/HVd+KKhsYFx1ObmrsgOdmHt5pqaM1YKW7AFjk4xGyvLR4HE6j6/fUUTQgU0oF3OSkmCEdV31zJ4QdTA3GrBRXQKaBAWAt6J+SFsf4hCifPk9emnXddael8qQBmVIq4FYszz9mR2BMhI0Vy/MD1KPg1NbVzc79zf3mH/OUmWwFvJocFpxOw8bSepb4KN2FJ3cusr0akI0ezTXwwPnQvD9gXdCATCkVcJctyOBTsyYc/n5CQhS/vnyO7rIcom1VTTicZtABWVxUOClxkZocFmszRGO73Sf1K3tKiYtkXHS4jpCNJuvugvL1sO63AeuCBmRKqVGhw+4k0lWq5ueXHa/B2DC4M/TPzUwa9GOykmN0hAwr3QXAUh9l6PckIuSlxWnKkdGibi8UPATGCYWPBGyUTAMypVTAGWPYUl7PmTPHA1BWqx9Uw1FY2UBGUsyQ1kBlpmhyWLDWj41PiCI7ZeDNEN6gAVmANVbBxvvgkSvhz4vAYbeOG2fARsk0IFNKBVzJoVbq2+ycNXMCSbERlGmOpmEpqmgY9HSlW1ZyLFX17TidYzsX2cbSepbmpgxqM4Q35KbFUd3YTkePdC/KR4yB6kJ469fwz9Phj8fBi9+FA5+A5/+5oytgo2QakCmlAm5zWT0AC7OTyUmN04BsGA61dFJZ3z7kgCwzOYYuh5P9zR2+6VgQqGpop6qh3S/rx9zy0uIwBso15Yjv2Dtg56vw/K3wh+Pg3jOs0a/waDj7p/CND2H6uRBmO/pxARol09JJSqmA21Jez7jocKaOjycnJZaCivpAdynouNePzRvqCJlriq6yvp1JiWMzzcgmV/4xf+ywdMtLs3ZalhxqZcbEBL89b8hrOQA710Dxy7D3LbC3QUQcTDsLZtxhBWDx44+cX7nRGhXz5OiCyg3+7TcakCmlRoEtZQ0szEkmLEzITY3lhY+q6ep2DlgcWx1RVNFAmMDxGeOG9LgsV+qLiro2vwYko8mGkjrio8KZNWlo124kcj0CMjUEzTXw1PVwxYOQMNGaijzwiRWA7XwFKjcBBsZlwvxrIP98yD0NwvtYV/n1d/3Z+35pQKaUCqjGdjs7DzRz4dxJAGSnxuE01jSSexRBDaywspEZExOIjRzar3V38t2xnPpiU2k9C3OSsYX5Z/0YwLjoCNLiIzX1xVC501M8/21IyoGdL0NDuXXf5IVw5o9gxnmQPufotWFBQAMypVRAFVY0YAwsyrHW77hL/pTWtmpANkjGGIoqGrhgTvqQHxsdYWPiuCgqxmjqi4a2Lor3N3PxvEl+f+7cVN1pOWhtdbD1f7D5AWuN185XwBYFU8+C075nBWEJQ3/9jyY+C8hEJBp4G4hyPc9Txpifikge8DiQCmwGrjPGdIlIFPAQsAioBa4yxpT6qn9KqdFhc1k9YXJk7VO2KyAr14X9g1Za20Zju515Q8g/5ikrOXbM5iJzbyhZHIDp2ty0ON7eedDvzxs0Du2C4peg+BWoWG8FYm5h4TDvc3DJnwPXPy/z5QKNTuAsY8w8YD5wnoicCPwW+KMxZhpQD9zgOv8GoN51/I+u85RSIa6gvJ6Z6eOIj7L+PhwfH0VspI1SzUU2aMNd0O+WmRwzZqcsN5TWEWGTIe9O9Ya8tDgONHfS2tnt9+celRzdUPourPkx/Hkh/HUxvPYT6GqGpV8HW+SRc53d8NETAS115G0+C8iMpcX1bYTrywBnAU+5jv8HuMx1+1LX97juP1v8lRBGKRUQDqehoLyBhTlJh4+JCNkpsTpCNgSFFQ3ERNiYPiF+WI/PSollX2M7dodz4JNDzKbSeuZkJBIdYRv4ZC9zT8mP6T8+Ohph29Pw9Fdg5VR48ELYcC8k58IFv4Nbt1kL7x2dxz42gElcfcGna8hExIY1LTkN+BuwB2gwxrj/HKgE3PVRMoAKAGNMt4g0Yk1rHurR5o3AjQDZ2dm+7L5Sysd27m+mpbP78Poxt9zUOHYdaA5Qr4JPYUUDczITCbcN72/srORYnAZqGjsOp8EYCzrsDj6qbODLp+YF5PndRcZLDrUye3JiQPoQEHUl1hqw4peg7H1rtCs2FfIvsHZFTj0TonqkAqncMGrSU/iKTwMyY4wDmC8iScCzwEwvtHkvcC/A4sWLx3ZqaaWCnHv9zqLso9fv5KTG8uaOAzicxq8734JRV7eTT6qb+NIpucNuI9Mj9cVYCsgKKxqwOwxLA5TuIzfNtYElFBf2e6aniEuz0lHsfNlKT3Fwh3XO+Jlw0s1WIJa5+NgErZ5GUXoKX/HLLktjTIOIvAWcBCSJSLhrlCwTqHKdVgVkAZUiEg4kYi3uV0qFqC3l9aTFR5GVcnRC0pzUOLocTmqaOshIGpvJSgdrR00TXQ7nsBf0w5HksGNtp6U7IWzPEVp/iY0MJ31cNHtDMSB785dQ9oE1BdleB2211kL8nJNh4Rch/zxImRLoXo4qvtxlOR6wu4KxGOBTWAv13wKuwNpp+UVgteshz7m+/8B1/5vGGB0BUyqEbSmrZ2F20jH1A3NcOy3Lals1IBvAkQX9w5/ympQYjS1MxlyR8Q2l9eRPTCApNnLgk30kLy0udEbIGiutEbCPV0GZa0SrdhfMvBhmXwbTzoGYpAB2cHTz5QjZJOA/rnVkYcCTxpgXROQT4HER+QVQANznOv8+4L8ishuoAz7nw74ppQLsUEsnpbVtXL302LWgRwKyNk6e6u+eBZfCikbS4qNGFLiG28JIHxdNxRiqq+hwGraU1XPp/MkB7UduWhxrPq4JaB+GzemEfQVWWoril2H/Vut4VAJImLXo3hYJ8RNgzhWB7WsQ8FlAZoz5CFjQy/G9wNJejncAV/qqP0qp0WWLe/1YL9NFkxJjiLSFje3dZ4NUWFHP/KzEY0YZhyorJYaKMTRCtn1fEy2d3SzNC2y5qLy0WOpau2hss5MYGxHQvgxKVxuUrHOVKloDLTVW8JV1Inzq/yBjCTz86SM5wxxdUPgInPFDq9SR6pNm6ldKBcSW8gYibMLxGcdOtdnChMyUGE19MYCmDjt7DrZy2fyMgU8eQFZyLG/vGjtJSt3rxwKRENZTXpqVqqSktpX5sUkB7UufmmtcuyJfgb1robsdIhOsgt35F8C0T0FcqnXuC989OoErHElPcdEf/N71YKIBmVIqILaU1TN7ct/5n3JT4yjVgKxfWysbgeEnhPWUmRzL/qZOOuyOgOTk8reNpfVkJMUEfI1inmunZcmhloAkp6W5BgoegUWzjoxgGQP7t1mjYMUvQ/UW63hiNiy8zkpNkXMqhPey9m4MpKfwFQ3IlFJ+19XtpKiygWtPzOnznOyUWD7cW4sxZsTTcaGq0L2gfwQ7LN3cO12rGtqZOn54CWaDwaqCKlau2UFVQwcxETZWFVRx2YKRjzAOV1ZKLGECJYcC9MfHurugqRLW/hpmXeQKwl6xjgFkLIaz7rBGwiYcN3DB7jGQnsJX+g3IRCQTa3H9acBkoB3YBrwIvGxMz3FJpZQa2PZ9TXR2O/tNN5CbGktrl4NDLV2MT4jyY++CR2FFA1PS4ryy9sid+qKyPnQDslUFVdz+zFba7Q4A2u0Obn/GWogeqKAsKtxGRnJMYHZa7v8EtjwEZrFVtHvzAxARC1POhGU/hOnLdd2XH/UZkInIA1jZ81/ASldxAIgGZgDnAT8WkduMMW/7o6NKqdDhTgi7MLvvgCzHlcW8vK5VA7JeGGMorGjg1GlpXmkvK9mViyyEd1quXFN8OBhza7c7WLmmOKCjZLmpcZT4IyAzBg4WH0nQWvHhkfskzEpL8dmHIEJTzQRCfyNkvzfGbOvl+DbgGRGJBLR2kVJqyDaXW+t30hOj+zzHnfqi9FAbi3ICu/B6NKpp6uBgcyfzMr1TcmdCQhSRtrCQTg5b3dD7LtK+jvvLlLQ4ntlS5ZvpeYfdKk/kLlVUX2odHz/LStTqdFUyNE4oeRs6mjQgC5D+ArLdIjLZGFPteVBEJgO1xphOYLdPe6eUCklbyuoH3N2WmWytrSkL4RGbkXAnhJ3fzyjjUISFCRnJMVTWhW7qi8lJMVT1EnxNDvDC/ty0OJo7u703Pd9eD7tet0bCdr0OnY1gi4IpZ8DJ34YZ58E7v4e6PUc/TndDBlR/Adm/gCeAahGZZIzZ5zq+ELgKuM7XnVNKhZ7qhnb2NXawKDup3/Miw8OYnBRDmeYi61VBhZU2ZNakhIFPHqTM5BgqQ3iEbMXyfL7/vyK6nUeKwMRE2FixPD+AvbKy9QOU1o5ger52jys32CvWiJhxQNx4OO5imHE+TFkGUR5rA3U35KjTX0A20xjzguv2iyLyS2PM065s+3f6oW9KqRC0pdy1fmwQ9QNzUmMp09QXvSqqaOC4SeOICvdeiorM5FjWVAdp1vhBuHT+ZH750ic0tnVjdziZnBTDiuX5AV0/BkcCspJDrSzpbeTYs1C3e5G90wEVG6xpyJ2vwKGd1vEJx8Gpt1pBWMYiCAvr/Uk9d0OuXQvLlnnpp1HD1V9A5hSRqcaYPYAAPwaeFpHpgO6uVEoNy+ayeqIjwpg1adyA5+akxvHy1n0DnjfWOJyGrZWNfGZRplfbzUqJoa61i9bObuKiQi8rUlFlIwebu/jN5XP4XC8luwIlIymG8DDpe2H/urugfD28+QuYdrY1ErbrVatod1gE5J4CS75iTUUm951KRo1u/b3jvge8LiKvAKmAEZF/YO2w/II/OqeUCj1byuqZl5lEhK2Pv9w95KTEUt9mp7HdTmJMEJSV8ZM9B1to7XJ4PZGoe6dlZX07+enemwodLZ7dUklkeBjnz5kU6K4cJdwWRnZqbO+pL6o2w5b/WOu7Ch6yvmKSYfq5VoLWqWdD9MB/3KjRr8+AzBjzrogsBi4GPgMY4EPgDmNMrZ/6p5QKIR12Bx9XN/HV06cM6vzDqS9q25jjpd2EoaCwvAHwToZ+T5nJ1uL2irq2kAvI7A4nz3+0j0/Nmjgqg/s8d+oLp9PKjO9eD7bfI9mBhFlTkZ99CGyhN4I51vX7P+oKvB4UkQ7X94/7pVdKqZD0UWUj3U7DokHuDHSnviira9WAzENhZQMJ0eHkuQJWb3Enhw3F1Bfrig9S19rFpwO8XqxXXa2ca9tMWN0rmN/fgLQeALHB5EXHpqbY8wa01WrC1hDUX2LYa4FHjTHO3gIxEZkKTDLGaJ0EpdSgHE4IO4gF/eARkOnC/qMUVTQwLzOJsDDv5qxKjYskJsJGZX3opb54tqCKlLhIzsgfH+iuWJqqjxTsLlnHVd0dNEkMHRnnEnP8xdZasTd/ATWFRz9OU1OErP5GyFKBAhHZDGwGDmJl6p8GnAEcAm7zeQ+VUiFjc1k9U9LiSInrpShxL2IjwxmfEKWpLzx02B3sqGnmpjOmer1tESEzOSbksvU3ttt5bft+rl6SNai1iz5hDNR8dKRg975C63hyLiy6nm3xJ/HpF+E/S0/hZHf1BU1NMab0t4bsbhH5K3AWcAowF6uW5XbgOmNMuX+6qJQKBcYYCsrrWZY/YUiPy02NpVRHyA7bVtWIw2m8vn7MLSsllooQGyF7ees+urqdXL7Qu7tSj9EzPYW9A0rfObIerKkKEMhaCmf/1CrYPT4fREhpaMf+4puU1LYeCci0UPeYMtAaMgfwmutLKaWGray2jdrWrn4LivcmOyWO93Yf8lGvgk+hK0O/t0om9ZSVHMPG0jqftB0ozxRUMWV8HHN9vQ5x3V1Q9gE8fQNEJ8Ket8DeChFxMO0sOPPH1u7I+GOnTdPHRRMVHhaYIuNqVNBtGkopv3CvHxtqQJabGsvTWzrosDuIjvBeEtRgVVTZyOTEaCaM67sO6EhkJsfS3NFNY5udxNjRtxtxqCrq2thQUsf3z53h/TqRYE1FHtgOW5+ETfcDxhoVi0+H+VdbuyJzT4WI/v+/wsLEf0XG1aikAZlSyi+2lNeTEBXO9AnxA5/sIdu1sL+8ro0ZE0MrFcNwFFU0MH+AslMjkZXiSn1R30ZibPDvbF1VUAXApfO9uLuyuwvK3nMtyn8ZGspcd7gCvrAImHkhXPj7ITWblxbHrgPN3uunCioDrm4UkbzBHFNKqf5sLqtnfvbQdwbmulI76FQO1LZ0Ul7XxrzMJJ89R+bh5LDBv27PGMOzBVUszUs5nNJj2NrqoOgJ+N+XYOVU+O9lsPlBmDALzvmZVbwbV41Mpx0KH4Hm/UN6ity0OMrr2uh2aDGcsWgwI2RPYxUU9/QUsMj73VFKhaLmDjvF+5s57/j0IT82x2OEbKz7qLIR8H5CWE/ubP0VdcG/sL+ospG9h1q5cZCJiI9xaNeRBfnlH1gpJ+InwuzLrAX5eWdAZCy88F0OB2Nuw0hPMSUtDrvDUN3QcXhkWI0d/eUhmwnMBhJF5HKPu8Zhpb9QSqlBKaxowJihrx8DSIqNJDEmglJNfUFhRQNhAnMyfDeVmBgbQUJ0eEgkh+2zVFJvxboBHN1Qsf5IEFa72zo+cQ6c9j1rPdjkBccW7PZSeopcd5Hx2lYNyMag/kbI8oGLgCSs8kluzcBXfdgnpVSI2VLWgAjDrr2YkxqryWGBosoGZkxM8Hnh76zk2KBPDnu4VNJxvZRKchfrXvdbOOensPt1K0Hrrleho8FaA5Z3OpzwdZixHJIGKETupfQUuWlWEFZysIUzZoySBLbKb/rLQ7YaWC0iJxljPvBjn5QalVYVVLFyTTHVDe1MTophxfJ8LhuNZVhGoc3l9eRPTCAheni79nJS4yhypXsYq4wxFFU0cO5xQ5/2HarM5Jig3+3nLpV0ec/3aHMNFDxsTSlufsBaB2YcEJNiTUPmnwdTz4Io/28gGR8fRXxUuObdG6MG82fWp0XkY6yksK9gJYj9jjHmYZ/2TKlRZFVBFbc/s5V2uwOAqoZ2bn9mK4AGZQNwOg0FZfVcPH/ysNvISYnlpa37sDucgcu0HmDldW3Ut9l9un7MLSsllnd2HcIY45tUEX7wbEEVqXGRnD5jPDgdULkJdr4Mmx4AR6d1knFC+ly4YCVkLoGwwKZVERFy02LZG+TBsBqewfxmO9cY04Q1fVmKVTpphS87pdRos3JN8eFgzK3d7mDlmuIA9Sh47DrQQnNn96ALivcmJzUWh9NQFeTTaCNxOCFslu9TUWQlx9Bud3CopWvgk0ehxnY7720v4wfZO4l4/mb43Qy4/1x4927obDr65EM7ITkv4MGYW15avO4oHqMGE5C55xguBP5njGn0YX+UGpWqG3oPBPo6ro7YUj60guK9yXGlvigbwzstiyoaiY4II98PudjcKSKCLvVFYyVs+Bet91/Kh7avcFXJj2DHCzBlGXzmPph/DYT1mBhy74YcJfJSY6msb6OrW1NfjDWDmbJ8XkR2YE1Z3iQi44EO33ZLqdFlclIMVb0EX5OTYgLQm+CyuayelLhIckewa8z9WKvI+Nhc7FxYUc+cjETC/TBl685FVlHfzoIRjGz6nNNpFekuftmajqyxlhGE2SbxXOQFXHHNV5Hsk8DmGld470+jvlh3blocTmNNUU8bYhJlFdwGDMiMMbeJyF1AozHGISJtwKW+75pSo8e3z5rGD11rxtxiImysWJ4foB4Fjy1l9SzMTh7RWqTxCVHERNjG7E5Lu8PJtuomvnBijl+eLzPZla0/0COSzTVQ8AgsmnUkPYW9HfauswKw4legpQYkDLJOgHN+xr70ZZz070q+f24+kjf96PaCoFh3XtqRRMgakI0tAwZknjnIPH6hNoqI0xhzwFcdU2o0iXLVUIyLstHa6WB8QhQ/vmCWLugfQF1rF3sPtXLl4qwRtSMirtQXY3NtTXFNM13dTr8s6AeIiwonNS4y8Kkv1t0FTZXw+p2QfaKVG2zPW9DdDpHxMO1sKzfY9HMhLhWAp97YBUjQvjfdAVmw73JVQzeYKcsbgJOAt1zfLwM2A3ki8n/GmP/6qG9KjRqrCquYnBjNQzcs5Zw/vM1t580M2l/4/lTgXj/mhdqL2SmxY/ZDyr2gf7h53IYjMzkmcGvIjIG9a2HLf8AsgaJHra/ELFh4Hcw4zyrYHR7V42FWqaQT8lIOT7sGm6TYSJJiIygZo398jGWDCcjCgVnGmP0AIjIReAg4AXgb0IBMhbTalk7e2XWIr542hdzUOCLDwyjerwWAB2NzWT3hYcJcL9RezE2LY+3OgzidZsj1MINdYUUDqXGRh6cS/SEzJZaPq/y4h6u7E0rfsaYhd74CjRVH7hMbHHcJXPEA9DP17S6V9LUzhlkqaZTIS4vTnZZj0GACsix3MOZywHWsTkTsPuqXUqPGi1v34XAaLlswmXBbGNMnxLOjRgOywdhcVs/syeOIiRx5SoHslFi6up3sb+5gUuLY2kxRVNHAvKwkv+YEy0qO5dWPa3wbALcesrLjF78Me96ErhYIj4Gck6z1Y07XR4xxWOe0HDi61FEPz26pJKq3UklBJi81jg/21ga6G8rPBrNdZ62IvCAiXxSRLwKrXcfigAaf9k6pUWB1YTX5ExOYmT4OgPz0BIprmgZ4lLI7nBRVNowo3YWn3FT3YuextbC/ucPO7oMtzPPCKONQZCbHYHcY9jd7cVO9MXCwGN79I9y3HH43HVbdBJUbYc4VcM2T8MMSKy9Yz+BzgPQUXd1Oniuq5pzjJjJumBUhRou8tDj2NXbQ3uUY+GQVMgYzQvZN4DPAKa7vHwKeNsYY4ExfdUyp0aCiro3NZfX84LwjuylnpifwzJYqGtq6SIqNDGDvRrcd+5rpsDtZ6KW0CTmu1Bflda2cNDXVK20Gg61VjRjjn4Swnty5yCrq2kc2IumwQ/kH1ghX8ctQX2IdT58Lp6+A/PMhfd7RBbuHUax73c6D1LfZjy2VFITcRcZLa1uZNWlcgHuj/GUwaS8M8JTrS6kx5bmiagAumXek7E++a6RsR00zJ04ZO4HBUG0uqwNgkZdGyCYlRhNhkzFX56+owlrH5c8F/WBl6wcrOezSvJT+T26ugaeuhysetKYU2+th9xtWALb7NehoBFsk5J0BJ99sLcpPzOy7Pc/0FGvXwrJlA/b32YLKI6WSgpxn6gsNyMaOwaa9+C0wARDXlzHG6KtEhTRjDKsKqliSm3zUjq2Z6Vam9B37mjQg68fm8gYmJUZ7LXluuC2MzORYysdYQFZYUU9uaqzfR2Pd/28VdYNIfbHuLij7AJ68zgq8yt631n3FpsHMi62C3VPOhCjf5NVqbLfz+vYDXLM0OyRqnbpHyHSn5dgymCnLu4CLjTHbfd0ZpUaTT/Y1setACz+/7Pijjk9IiCIpNkJ3Wg7AnRDWm3JSYykdYx9SRRWNnDBlgBEqH4iOsDFxXBQVfaW+cDqgYgNsewo23Q8YqPgQUqfDKbdYU5EZi/xSI/Klrfvo6nZy+cLgn64EiI8KZ3xCFCUHx9ZrfawbTEC2X4MxNRY9V1hNeJhwYY8dWyJC/sQE3WnZj5rGDqoa2vnyqXlebTcnJZbNpfUYY/y64zBQaho7qGnq8PuCfres5Nijc5F1NltTkTtfsXZHttViTZq4hEVA3ulwzk/92s9nt1QxdXwcczL8u87Ol/LS4sbcHx9j3WACsk0i8gSwCuh0HzTGPOOrTikVaE6n4bmiak6fMZ6UuGOnimamJ/DU5soxmRNrMNwFxb21fswtJzWO5s5u6lq7SI2PGvgBQa6osgGA+V5IrDscmckxlJcUw4dbrVJFpe9ai+ujk6zs+NknwprbrRxiYKWpKHwEzvhhv+kpvKmiro0NpXWsWJ4fUkF6Xmocb+zYP/CJKmQMJiAbB7QB53ocM4AGZCpkbSitY19jB7edP7PX+/PTx9Ha5aCqof3wbjR1xOayeqLCwzjOywuS3TstS2vbxkRAVljRQHiYeP069svphOoC2PkyPyp/lgmdu+FlIHUaLL0R8i+w6kbawuGF71qpLDy501Nc9Ae/dHdVQRUAl86fPMCZwSU3LY5DLV00d9hJCPI0HmpwBrPL8np/dESp0WR1YRWxkTY+dVzvf+Xnuxf21zRrQNaLLeX1zM1MJDLcuwusc1y5yMrrWr0++jYaFVU0MGvSOKIjvLQOq+duSLeuNqtU0c6XYecaaNlvFexOXsgvGj/Pl6+/icnT5hzb3jDSU3iTMYZngrxUUl+O7LRsY05m6EzFqr4NZpflDOAfwERjzPEiMhe4xBjzC5/3TqkA6Ox28NLWGs49biKxkb2/RdwBWXFNU59B21jVYXewrarR6+vHALJSYhAZG8lhnU7DR5WNXLbAiyM/6+6C8vXWCNbpK6y1YDtfsYKx7g6IGmcV7M6/AKadw+5qJ//+94ecxSR67YVneooAKKxooORQK18P8lJJvXEHZHsPtWhANkYMZsryX8AK4J8AxpiPRORRQAMyFZLWFR+ksd3Opf0kmIyPCicrJUYX9vdiW1UjdodhkZd3WAJEhduYnBhDeV3oB2R7D7XQ0tnN/CwvXcemfVDwX2tKcdP9sOk+63hSDiz6krUrMvtkCD+yZjIrxbrOfe60DLBnC6pColRSb3JSY8fMHx/KMpiALNYYs6HHYsluH/VHqYBbXVRNSlwkp05L6/e8/InjKNaA7Biby6wF/d4qmdRTdsrYSH1RUN4AwPyRZOi3d1gL8YtfgqLHj55ezFgMl/4Vxs/ss2D3pMRobGEyuFxkftbV7eT5omo+FQKlknoTHWH98TEWXuvKMpiA7JCITMVayI+IXAHs82mvlAqQ5g47r3+yn6uWZA2YYHJmegJvFR+gs9tBVLjvcy0Fiy3l9eSkxpLmo0X3uWmxvPpx6O8+K6psID4qnClpQ0ym2nIQdq1xFex+C+ytVsFuR6fHSQb2b4OYlD6DMbCS8U5KjD469cUocbhUUojkHutNblosew9pQDZWDLaW5b3ATBGpAkqAz/u0V0oFyJqP99PZ7RzUjq389AQcTsOeA60cN1kLV4C1yHpzWQOnT+9/dHEkslPiqG0N/d1nRRWNzM1MHDitijFwcIc1Clb8ilWoGwPjMmDe56ypyO0vQNGjR4+QDXI3ZGZyDBX1o2+EzF0q6bTpwV8qqS95aXE8V1g9ZvLujXX9BmQiYgO+YYw5R0TigDBjjM7RqJC1urCKrJSYQWWYd5dQKt7fpAGZS0VdO4daOn02XQmQ60p9UVbbxvEhlAjUbVVBFXe9soPqxg7io8JZVVDFZT3XMzrsUPaeFYAVvwQNZdbxSfNh2e1WqaL0uUdGv9742bB3Q2Ylx7Ju58GR/2BeFGqlkvqSmxpHU0c39W32XvMhqtDSb0BmjHGIyKmu20MaNxWRLOAhYCLWdOe9xpi7RSQFeALIBUqBzxpj6sUK/+8GLsDKe/YlY8yWof04Sg3fgeYO3tt9iG8smzaov0Zz0+KItIXpwn4Pm8u9W1C8N9khHJCtKqji9me2Em8/xBORf+Hmzm9z+zNbAbgsPwZ2v+4q2P06dDZBeDRMWQanfscq2D2uj8XtI9gNmZUSy4HmTjrsDu+l3xihUCuV1Bf3TsuSQ60akI0Bg5myLBCR54D/AYeDskFk6u8GvmeM2SIiCcBmEXkN+BLwhjHmNyJyG3Ab8EPgfGC66+sErFQbJwzx51Fq2F78aB9OM/gEkxG2MKZOiGfHPg3I3LaUWeueZkxM8NlzuHORldWF3tqalWuKabc7+FH4syyRYn4c/jDbnHlkP/d/wA6rYHfcBJh9Gcw43wrGIn2bfysz2SoyXtXQztTxvikOPlTPbKkMuVJJvTmSi2xs5N0b6wYTkEUDtcBZHscGzNRvjNmHa/G/MaZZRLYDGcClwDLXaf8B1mIFZJcCDxljDLBeRJJEZJKrHaV8blVhNcdNGsf0IQQTM9MT+GBPrQ97FVw2l9UzPysJmw/LScVHhZMWH0lZCKYD2N/QwrmymattbxImhsvC3+cy3me7IxvO+I6VH2zyAgjz3zSdO/FxRV3bqAjIKura2FhaH3KlknqTlRKLLUwo0YX9Y4JfMvWLSC6wAPgQK8GsO8iqwZrSBCtYq/B4WKXr2FEBmYjcCNwIkJ2dPdKuKQVYf4EWVTRwex+lkvqSn57AswVVNLbZSYwN3QXmg9HS2c2OmiZuPmu6z58rJzUudEbIOhoPF+zeHP0iibQcrkbUbcJY7TiJP8R/n/fOPqv/dnwky5UBv3KULOx/1lUq6Zh1dSEowhZGVnIMJZr6YkwYTKb+KVhru07EGhn7ALjVGFMymCcQkXjgaddjmjz/ojHGGBExfT64F8aYe7F2fbJ48eIhPVapvqwurEYELhliPbwjJZSaOGFKqi+6FjQ+qmjAaWChHwph56TE8sHeIB6ZrC+1FuTvfBlK37OKcsek0Dz5FGKqXidSHACEi5MLbRuJPSMlYF2dkBBFpC1sVCSHNcbwbEEVJ05JISMpJtDd8YvctDhKDmpANhYMZtz7UeBJYBIwGWst2eODaVxEIrCCsUc81pztF5FJrvsnAQdcx6uALI+HZ7qOKeVTxhhWF1axNDeFSYlD+yV/ZKelriNzJ4Rd4IMM/T3lpMaxr7GDDrvD58/lFU4nVGyE138Gfz8J7p4Hr/zQyp5/0jfg+ldgxW4yJ2cekxcsIsxwfu1DAeo4hIUJGckxVI6C5LDuUkmXL8gMdFf8Jjc1jtLaVkzPIu4q5Aw2U/9/Pb5/WERWDPQg167J+4DtxhjPRDfPAV8EfuP6d7XH8ZtF5HGsxfyNun5M+cO2qib2Hmrlq6cPvR5e+rhoxkWH605LYHN5PTMmxpMY4/up25zUI+uahrLmz686W2DvW9ZI2K410HoQxAY5J8PyX1m7IlOnHvUQe9l6InsUQrEZu9+KdfclMzlmVCSHPVIqKT3QXfGbKePjaOtycLC5kwnjogPdHeVDfQZkrvQUAC+7dkM+jjVleRXw0iDaPgW4DtgqIoWuYz/CCsSeFJEbgDLgs677XsJKebEbK+3FiNeuKTUYqwqriLAJFxw/9Hp4IsLMdC2h5HQatpTVc+Fc/9QUzPFIfRHQgKy5BgoegUWzIGEiNFZZ05DFr0DJ21Z2/KhEmH6Oq2D32RDT9wjig3Me5pcvbefN753BlFGwgN4tMzmWNdU1Ae2DZ6mkUE4I3FNuqrvIeKsGZCGuvxGyzVgBmHv8/Gse9xng9v4aNsa86/HYns7u5XyDVRVAKb9xOA3PF1WzLH/CsBflz5yUwLNbqsZ0Nu29h1po6uj2y3QlHEl9EfA6f+t+C40V8NhV4HRAzUfW8eQ8WHKDq2D3SWAb3GvruaJq5mYmjqpgDCArJYa61i5aO7uJixrMxIr3jYVSSb3xTH1x4hhfpxrq+nxnGWPy/NkRpQJh/d5aDjR3ctn84f+Sz09PoLmzm6qGdjKTfZsTarRyrx/zV66k5NgIEqLDKa8LwDSavd0a/dr2FHz0JHASVBfA5IVwzp3WSFjajH5rRPZmz8EWtlY1cseFs3zS7ZFw77SsqG9jZnpgqlI8syX0SyX1ZnJSDJG2ME19MQYMZpdlNPAN4FSskbF3gHuMMR0+7ptSPre6sIr4qHDOnjVh2G0cXthf0zymA7Kk2AimuP6a9zURISc1ltJaPwVkzfuPLtjd3Q5h4RyeBLBFWPnBTv3OsJ/iOddO34vnDW2nrz+4k8NW1rUHJCBrbLPzxvYDfP7E0C6V1BtbmJCdGqsB2RgwmFf2Q8Bs4C/AX123/9vvI5QKAh12By9vrWH57PQRlYRxZ6Ufywv7N5fVsyg72a9TtjmpcZT7asrSGKjZBm+vhH+dBb+fAc99C/Z9BAuuhcv/7QrIXDvfHHYofMQK3Ib1dIbniqo5MS+ViaNwndDh5LABWtj/4tZ9dDmcY2p3pduqgioq69p49ZP9nPKbN1lVoMkHQtVgFgMcb4w5zuP7t0TkE191SCl/eWvHAZo7uwddKqkvCdERZCTFjNmF/Q1tXew52MrlC/37YZmbGsuabTV0O5yEe2PUpLsTSt+Fna9Yi/Iby63jkxfCmXdYBbsnHm9NRb7wXTDOox9vnNaasov+cGzbA9hW1UTJoVa+Noydvv6QGhdJTISNigClvni2oJJpE+I5PiMw06WB4q5t2tFtvdaqGtqP1DYdA4lxx5rBBGRbROREY8x6ABE5Adjk224p5XurC6tJi4/i5KkjXyg7Mz1hzAZkBeUNACz004J+t5yUOLqdhuqGjsMFx/vUXANPXQ9XPGjthnRrrYVdr1o7I3e/CV3NEB5j1Yg8/fswYzkk9JJioXIDOLqOPuboGnZ6itWunb7nD2Onrz+ISMBSXzS229lY2jomSiX15K5t6qnd7mDlmmINyELQYAKyRcD7IuL6c5FsoFhEtmJtjpzrs94p5SON7Xbe3GGtSfHG6Ep+egLrdh6kq9tJZPjYWuOyuaweW5gwL8u/hZ7dqS9Ka1sHDsjW3QXl660RrBO+DsUvWSNhFR9aI1vx6XD85daC/LzTBy7Y/fV3j9xeuxaWLRv2z+FwGp7/qJozZgx/p68/ZKXEUuHH8kmrCqpYuaaY8S0lQAaxkcNfVhCsqht6v959HVfBbTAB2Xk+74XyCvcvsOqGdiYnxbBieb7+FdWHNdtq6HI4uXQEuys95acn0O007DnYwqxJY2taZXNZPbMmJRAb6d90CO7UF2UD7bRsqICC/1qB16b7YdN91vH0OXDa963UFJPm+7Vgt6cPS2rZ39TJHReOvsX8nrKSY9hYUueX9C7uqbp2u4PxrpfVXa8UkxwbOaZ+p01OiqGql+Br8hgpGzXWDKa4eJmIzANOcx16xxhT5NtuqaHy/AUGutZgIKsKq8hNjWVepndGddw7z4prmsdUQNbtcFJU2cCVi/y/2HpCQhTREWGU9bb7rL0Bdr9u7Yrc/tzR04vZJ8Pl90JS1rGPC4Dni6qJjbRxzqyJA58cQFkpsTR3dtPU3u3zkTydqrOsWJ5/1O91gJgIGyuW5wewV8pXBpP24hbgq4C7FuXDInKvMeYvPu2ZGhL9BTZ4+5s6+GBvLd86a7rX/tKfMj6OCJuMuZ2WO2qaaetysNBP+cc8hYUJ2SmxR0bI6vZai/GLX4LyD8DZbWXFd3q+LwxUbwFbpN/725vObgcvuXb6xozyKTl36ouK+jYSY307Pa1TdRb3726d+RgbBjPHcANwgjGmFUBEfgt8gJUGQ40S+gts8J4vqsYYRry70lOELYyp4+MprmnyWpvBYEu5fxPCHsXp4Ky4EnKr3oa/boNDxdbx8TPh5G/BjPOh6HEofBgcHkHZCHZDetvbOw/R2G7nklGYe6wnd469iro2js/wbUCmU3VHXLYgQwOwMWIwAZkAnn9iOui7JJIKkPEJURxo7jzm+Fj8BTaQ1YXVzMlIZKqXy9PkpyewsaTOq22OdpvL6pmQEEWGv15nnc2w583DBbtva6vFbmyYSacgi6+3CnaneBQZeel7Xt0N6W2rC6tIjo3g1Olpge7KgNy5yCr9sLB/xfJ8VjxVhN1hDh/TqToV6gYTkD0AfCgiz7q+vwy4z2c9UsPSW0Cmv8CO5cvyNPnpCawurKax3U5izOjdLedNW8rrWZTjxYSwvaWnaKhw5QZ7GUrfsQKq6CSY/ineDlvCzR8m8+qnLyE9sZeEqp67IUeZ1s5uXt++nysWZQZF9vnEGKtclT+Sw146fzK/emk79W1dCJChU3VqDBjMov4/iMharNJJANcbYwp82is1JEUVDXxc3cQFx6fzwd5a6tvsjE+I4scXzNJfYD2sLqhCBJ9MEblLKO3c38yS3BSvtz/aHGjqoKKunS+elOu9Rt3pKV5aAeNnWCNh+63NKaRMhaU3Wrsis04EWzjsPEjThxsoq23tPSAbxV77ZD8ddu/t9PWHrORYKvxQP/TDkjoONHey8oq5jG+JZdkI0oooFSwGtU/dGLMF2OLjvqhh+v1rO0mOjeCuK+fR0tHNib9+g6+dPkWDsR6MMawuqubkqalM8EF5GvdOyx01YyMgc68f88qC/q42+PhZ2PygtcZr+2rYLpB9Enzq/1wFu6cf87Bcd+qL2jZOmDLyBL/+tLqwismJ0Szyc0LdkchKiWHvQd/XVHx4fRmJMRFcPG8y69/b4/PnU2o08G/iIOV1G0vreHvnQX50wUzio8KJjwonKyWGjaV1fOW00VmGJVAKKxooq23jm2dO80n7kxKjSYgOHzML+7eUNxBpC2P25GGm+WiuOTIVuXctdHccuS/MBnOvhsv+1m8Tk5OiCQ8TyuqCq/ByXWsX7+w6xA2n5REWFjxLcjOTY3l75yGf5iI72NzJmo9r+MJJuSOqMatUsNGALIgZY/jdmmLGJ0Rx3Ym5h48vyU1hXfFBvyRwDCarC6uJDA/jvON7KYXjBSIypkoobS6rZ05mIlHhg/zQNAZqtrqCsJeg2rXyISkbjr8Ctj55ZAG+0wHbnoKzf3J0qaMewm1hZCbHUFobmKLXw/XS1n10Ow2XzguuUeys5Bja7Q4OtXQxPiHKJ8/x5KYK7A7D50/I9kn7So1Wo38lqerT+3tq+bCkjm8um3pUDqOluSnUtloFn5Wl2+HkhY+qOXvmBMZF+27BfX56AjtqmjHGDHxyEOvsdrC1snHgdBfdnbDrdXjxe/DH4+Gfp8Fbv4KwcDjr/8FN78MtH0F4Lx/u7vQUA8hOjaM8yAKy5wqrmT4hnlmTEgLdlSFx77T01cJ+h9Pw6IflnDItlSle3gWt1GinI2RByhjD718tZnJiNFf3+EtySZ61fmljaR3TJugvNbCC10MtXV7NPdab/PRxNHeUs6+xI2RTjqwqqOIXL26ny+Hkqc0VHDdp3NHrFVsPwc41Rwp221shIhamngXLbrMKdsdPOLrRERTrzk2NpaC8PmhGhKsa2tlQWsf3PjUjKPrryZ2LrLK+3SfF5NcWH6Cqod0nu6CVGu00IAtSa4sPsqW8gV99es4xU0ZT0uJIi49kY2kdVy/VYX+wSiUlRIezLH/CwCePgHun5Y6appAMyNwluuLth3gi8i/c3Pptbn/mIxKadnF22BZXwe4NgIGEyTDvKitBa97pENHPRooRpKfITomluaObhjY7yXGjIwN/f14oqgbgEh//ceALh7P1+2in5cPry5iQEMU5x43uMlJK+YIGZEHIGMPvXysmOyWWKxcfW0NQRFick8LG0rGVpLQv7V0O1myr4cK5k3y+SHjGRHdA1sxZM0PvQ8VdouvH4U+zRIp5KPLXxNJJzlsHrBMmzXeNgp0Hk+aBH0aA3DstS2tbgyIgW11YzfyspMPF0YNJXFQ4qXGRVPpgyrKiro21Ow/yrbOmB0VeNqW8TV/1QWjNx/vZVtXELWf3/YtrSV4KFXXt1DR29Hr/WPLGjv20djm4zA/5nhJjIpicGB2aC/vb61nc9Dr3RvyOz9veJEwMM6WCcjOBH9lvgO9uh6+tswKyyfP9EowB5KRa02jlfsiPNVK79jfzyb4mn0+d+1JmcoxPsvU/8mE5YSJcvXR0FH1Xyt90hCzIOJ2GP762kynj4/rNM7bUlQdrQ2ldUNTJ86VVBdVMHBfltzxV+aG007J2j5WWovhlKP+AuyMdtJtInAg2DF3YKDHprEu4CMYF5nWWlRKLCJQeGv0B2XNF1YQJXDh3UqC7MmyZKbF8XNXo1TY7ux08uamCs2dOYFJi6E31KzUYOkIWZF7Yuo/i/c1855wZ2PrJXzRrUgJxkbYxV1uxp4a2LtbtPMDFcyf3e728KT99HHsOtmB3OP3yfF7l6Iay9+HV/wd/WQx/WQiv/hja6+HU7/DW4r8gGGxi7SKNEgeftb3NHWcELhFudISN9HHRoz4XmTGG54qqOXlqGhMSgquqgKes5FiqGtpxOL23k/iVbTXUtXZx7Yk5XmtTqWCjI2RBpNvh5E+v7WRmegIXzun/L+xwWxgLc5LH/Dqyl7bWYHcYv1YtmJmegN1h2Huwlfz0IEhr0NEEe944XLCb9noIi4DcU61SRTOWQ7L1QZn2zxsQjv4gjggznF/7EDDf/313yUmNpWyUp74oqmz0aWJif8lMjsHuMBxo7vDaaNbD68vISY3l1Gmjv8i6Ur6iAVkQebagir2HWvnndYsGld17aW4Kf3h9J41tdhJjx0ax655WF1YxZXzc8LPJD0O+x07LgAdkzTVQ8AgsmnV0gtX6Mo+C3e+C0w4xKTB9uVUrcupZEH30NWvr6iZi3yaipPuo4zZjH1R6Cl/KSYnjjR37A9qHgawurPJpYmJ/OZyLrK7dKwHZjpomNpbW86MLZgZV1QKlvE0DsiDR1e3kz2/uYk5GIucOckv4krwUjIFNZXWcPSv0dvwNpLqhnQ9L6viun/M9TR0fT3iYjI51ZOvugqZKK8Hq/GusDPnFr8CBj63702bAiTdZtSKzlloli/rw6Ifl/KLjVzx900ksyhldtTpz0mI51NJFS2c38VGj79eaw2l44aN9nJk/3qeJif0hyyP1xdK8kb8OHllfTmR4GFcu0sX8amwbfb+5VK/+t7mCirp2/u/64wcdXMzPSiLCJmwoHZsB2fPufE9+3tQQGR7GlPFxgQ/I6vZCwUNgFsOm+6wvsUHOyXDuL62RsNSpg2qqw+7g3rf3cuKUlFEXjIE1QgZQVtvK7MmJAe7NsdbvreVgcyeX+mGnr6+58+t5Y6dla2c3zxZUcdGcSUGRskQpX9KALAh02B385Y3dLMpJZtmM8YN+XHSEjbmZSWN2Yf8qV76n3DT/53uamT6OzWX1fn9emqqPTEXueh1wbywIs5KzfvZBiBl6hvWnNldyoLmTP14134ud9Z7DqS9q20ZlQLa6sIr4qHDOmunbxMT+EB1hY+K4KK+UT1pVWEVLZzef18X8SmlAFgwe21BOTVMHf7hq3pCn3hbnJnP/uyV02B0+T4o6WqwqqOJXL23nQHMniTHhrCqo8uuifrDWkT1XVE1zh50EX05RGQP7io4U7N5XZB1PzLTygB1ef++EivXQ3dVXS32yO5zcs24P87OSOHmqf1KHDJU7IBuNRcY77A5e3lbD8tnpIfMezEqOHXG2fmMMD68vZ9akcSzMTvJOx5QKYpr2YpRr73Lwt7f2cNKUVE6eOvQdSEtzU7A7DAXlDd7v3CjkLu1zoLkTgMb2bm5/ZiurCqr82g93CaWd+30wbWnvgJ2vwgvfgT8cB/eeAWt/A+HRcM6d8I0PYfq5x64HG2Sx7p5WF1ZTWd/OzWdOG7W1FxOiI0iNi6R8FKa+WFt8kOaO7qAsldSXrJTYEU9ZbilvYPu+Jq49MXvUvq6U8icdIRvlHvqglEMtndxz7cJhPX5xTgoiVqHxk0bp6IY3uUv7eGq3O1i5ptivo2RHdlo2e2fNVcsBq2B38cuw9y2wt0FEHEw7C/L/nxWAxXkE7JUbh12s+6iHOA1/X7ubWZPGcfas0T3dlp0aOyqTwz5fVE1qXCSnhND7LzM5htWF7dgdzmGXOXpkfRnxUeF+qaChVDDQgGwUa+6wc8+6PZwxYzyLc4f3oZ4YG0H+xIQxk4+suqH3v9r7Ou4rGUkxJESFs2PfIEfImmvgqevhiget9BTGwIFPjmTJr9oMGBiXae2WzD8fck+D8Kje2/Ms1r12LSxbNqyf4+Vt+9h7sJW/XrNg1I9i5KbGsWGUrZds7rDz+vb9fG5JFuEhVJ8xKzkWp4F9DR1ku6aLh6K+tYsXtu7jqsVZxI3CXbFKBYK+E0axB94rpb7NzvfOnTGidpbkpvDMlkq6Hc6Q+lDozeSkGKp6Cb7cO8P8RUSYMZQSSuvugvL18Py3ISkHdr4MDeXWfZMXwpk/sgp2p8/xW41IYwx/e2sPU8bHcf7xo7/UT3ZKLKsKq+jsdhAVPjrWar368X46u51cEmKjQJkp7p2WbcMKyP63uYKubqdm5lfKQ2h/OgexxjY7/3pnL+ceN5G5mUkjamtJXgqtXQ4+2dfknc6NYt8889g0DjERNlYsz/d7X/LTE9hR04Qx/ZSYaauDD/8Jmx+w1njtfAU2PwgTZsPFd8N3d8CNb8EZP4BJc/0WjAG8ueMA2/c18Y1l0/xWdmokctNiMcZKWDparC6qJjM5JuQWrWclu5LDDmOnpdNpeOTDcpbkJgc+cbJSo4iOkI1S/3pnL80d3XznUyMbHQOPQuMldSMO7ka7bld9vfEJURxq7mRyUgwrluf7fZclWAv7H/2wm5omjxIzxsChXdYIWPHLUPGhFYi5hYXDvM/BJX/2e389GWP4y5u7yUyO4dIgWYye7ZGLbNqE+AD3Bg61dPLe7kN87fQpo366d6gmJUZjC5NhBb/v7j5EWW0b3/XC7zalQokGZKNQbUsnD7xXwkVzJzFr0shL/qQnRpOVEsPG0jq+ctoUL/RwdDLG8NiGCo7PGMcL3zot0N0hf6L1139xdT2T6jYdyQ9Wt8c6YeIcWPp12PTvIwvwnd3w0RNw5o+PLnXkZ+/vqaWwooFfXHb8sBdt+1uua+pstNS0fGnrPhxOExLJYHsKt4UxKTF6WCNkD68vIzUuMuhLSCnlbcHxm3aM+efbe2m3O7j1HO/9BbkkN4VNpfX9T58FuW1VTWzf18RVi0dBCZb2BubUv86fIv7KiU+fAP+5CDbcC8m5cMHv4NZtcNO74Og89rHDTE/hTX95cxcTEqK4YlFmQPsxFClxkcRHhVNWOzpSX6wurGZmekLITstlJscMOfXFvsZ2Xt++nysXZ42adX5KjRY6QjbKHGjq4D/vl3LZggyvTrsszU3hmS1WcfKp4wM/neMLj28sJyo8LHALqOv2WnUid74MZe8T6+zmDNs4Poo7maXLr7EKdkf1+HCu3OCV9BTetLmsjvV767jjwllBlchURMhJjaVshAlLvaGiro3NZfUBWbvoL1nJsazbeXBIj3lsQwUG+PwJ2b7plFJBTAOyUebva/fgcBpuOXu6V9td4ioCvLGkLiQDsvYuB88VVnPhnEkkxvgwM75neoq4NKjcZGXI3/kKHNxhnTN+Jpx0M+RfwHdec7K/pZuXj+tjCtUzPcUo8dc3d5MSF8k1QfihmZMay/bBphrxoec/CkwdVX/KSonlQHPnoKuA2B1OHt9QzhkzxpOVMvSdmUqFOg3IRpGqhnYe/bCcKxdnkpPq3fqLU9LiSIuPZENpHZ9bGnwftAN5aes+mju7+ewSH09XvvlLKPsAHrwQ2uugrdZaiJ9zMiz8IuSfBylH1unlT9rO+++VjiiBpj9tq2rkreKDfP/cGcRGBt+vh5zUOF77ZH/AU7w8V1jNopzkkA48MpOtjSpVDe2D+iPv9U/2c6C5k1+doKkulOpN8P3GDWF/fXM3ADef5d3RMbCmcxbnpIRsgtgnNlaQmxrLCXleyIrfU2OltRj/k9VQ+o51rHYXzLwYZl8G086BmKReH5qfnkCXw0npoVamTxz9a4n+9tZuEqLD+cLJuYHuyrDkpMRidxj2NXYELBjaUdPEjppm/u/S2QF5fn9xX9+KurZBBWQPf1hGRlIMZ4ZAgXWlfEEDslGirLaV/22q4NoTc8jwURLTJXkpvPJxDTWNHaQnRvvkOQJh78EWNpTW8cPzZnonvYDTCfsKrSBs58tQs9U6HpUAEmYturdFQvwEmHNFv03NTLd2ye6oaR71Admu/c288nEN31w2jXG+LIjuQ+6R5bLatoAFZM8VVmMLEy6YM/qT6Y7EkVxkAy/s33uwhfd21/L9c2cERU47pQJh9M+hjBF3v7ELW5jwjWXHJjb1lsP5yEJslOyJTRXYwoTPLBrBYv6uNisAe+7b8IdZ8K8z4Z3fQWQ8fOr/4Esvg8N+JGeYowsKH4Hm/f02O3VCHLYwGXzG/gD6+9o9RIfb+PKpeYHuyrDluFJflAZop6UxhueKqjllWhpp8X2UtQoRExKiiLSFUTmI1BePfFhOeJj4fkmBUkFMR8hGgd0HWlhVUMVXTpvChHG+G7maNSmBuEgbG0vqQmaxsd3h5OnNlZw1cwITEoZ47ZprXLnBXoG9a6G7HSITrILdM853Fex2FYR+4btHJ3CFI+kpLvpDn08RFW5jSlocO0Z5QFZW28pzRdVcf3IuKXGRge7OsKWPiyYyPIzyAO203FLeQGV9O9/xYsqa0SosTMhIjqFygOSwHXYHT22uZPnx6UN/jyo1hmhANgr86fWdxETY+Nrpvk3aGm4LY2FOckitI3tzxwEOtXTxuZ5/efcs1g1Wlvz926wArPglqN5iHU/MhoXXWbUic0/tvWD3CNJT5KcnUFjRMOSfzZ/uWbcHmwhf9fFr0NfCwoTslFhKDwVmhOy5wiqiwsM4d3bgkvr6U2ZyzIDJYZ8vqqax3c61uphfqX5pQBZg2/c18cJH+7j5zGmk+mGKY0luCn98fSeNbXYSY4NznZCnJzZWMHFcFGfMGH/0He5i3Wt/DbMucuUHewUaK6z7MxbBWXdYI2ETZw9cI3IE6Slmpifwwkf7aOnsJj5q9L3l9jW289TmSq5aksVEH47Q+ktuamxARsi6HU5e3LqPs2dNICFI1+ANVWZyLB9X1/R7zsMfljNtQjwnTvHBhhulQsjo+3QYY/742k4SosP5qp9KGi3JTcEY2FRWx9mzgvuv+H2N7awtPsBNy6YeneJg/yew5SFrSnHzA9ZXeIyVmPWMH8D05X4tS5TvWthfXNPMopxkvz3vYN379l6cBr52uu/WL/pTdkoc7+2uxRjj1xqS7++p5VBLF5fMC71SSX3JSomhrrWL1s5u4nr5Y2NbVSNFFQ389OLjQq6ep1LepgFZAH1U2cCrn+znu5+a4bfRqgXZSUTYhA2lwR+QPbWpEqeBzy7KhAM7XAW7X4GK9UdOkjArLcVnH4II3+xeHchMV+mc0RiQHWrp5LEN5Vw2PyNkcmblpsXSbndwsLnTp2sye1pdWE1CdDjL8scPfHKIOLLTsu3wjmJPD68vIybCxuULg6cEl1KB4rNdliJyv4gcEJFtHsdSROQ1Ednl+jfZdVxE5M8isltEPhKRhb7q12jyh9d2khwbwfWn5PrtOaMjbMzJSGRjSXCvI3Pau9i14SX+nvo/ch45Ff5+Arx+J3Q0Wola3YwTSt6GjqaA9TUjKYa4SBvFNYHrQ1/ue7eEzm4n3zgzNEbHALJT3Dst/Tdt2WF3sObjGs4/Pj2oyk2NlDuI721hf1OHndWF1Vwyb7Jvq2coFSJ8mfbiQeC8HsduA94wxkwH3nB9D3A+MN31dSPwDx/2K6BWFVRxym/eJO+2F1lbfJDTpqX5fb3JkrwUtlY10mF3+PV5R6y9Hj76Hzz1ZZx3TeHPnT9hefuLkDoNLvwDfOcTK2O+9HhZB7hYd1iYMCM9YdTttGxss/PfD8q4YM6kkCqnlXs4F5n/Fva/ueMALZ3dY2q6Eo5k6+9tYf8zmytptzu49kRdzK/UYPhsytIY87aI5PY4fCmwzHX7P8Ba4Ieu4w8ZYwywXkSSRGSSMWafr/oXCKsKqrj9ma20ewRCr27fz6qCKi5b4L9f5EtzU/jnur0UlDdw0tRUvz3vsNTucSVofQXK3gfjgLjxbIw9jScaZ/Ob730LW1zikfNHYbFusKYtX95W4/d1Tf158P1SWjq7ufnMaYHuildlJMdgCxPK/DhC9lxhNWnxUaP//eRlqXGRxETYqOgxQmaM4eEPy5mXmciczMQ+Hq2U8uTvNWQTPYKsGsC9iCkDqPA4r9J1LKQCspVrio8KxgA67E5Wrin2a0C2OCcFEdhYWhf4D5DmGih4BBbNshbaOx1QseFIwe5DO63zJhwHp94KM86nPnkOX/z1W1xzQjbRcT1+2Y/CYt0A+RMTeGxDBQeaO0fFTsaWzm4eeL+Ec2ZNYNakY9f+BLMIWxgZSTGU+WmnZYfdwZvFB/j8CdljLgu9iJCVcmzqiw9L6th9oIW7rpgboJ4pFXwCtqjfGGNExAz1cSJyI9a0JtnZwVUku7qh9wSKfR33lcTYCPInJoyOfGTr7rJSUaz6OsRNgF2vWkW7wyIg9xRY8hWYsRyScw8/ZNV7JXQ5nFwVRFm/8z1KKI2GgOyR9WU0tNn5ZoiNjrnlpMb6bcpyz8EWurrDuXT+2JqudMtMjqWyR/mkh9eXMS46nIvnhkYCaqX8wd8B2X73VKSITAIOuI5XAZ6frpmuY8cwxtwL3AuwePHiIQd0gTQ5KYaqXoKvyT6qXdmfJbkpPLOlkm6H8+iUEf7SUA5FT1opKTgB9rwJ0YlWctb882Hq2RB97MiNMYbHN1QwNzMxqEZ2juy0bDo2Z5qfddgd/OudEk6dlsaC7NG169NbclJjeb7ItwPsqwqqWLmmmPEt+7GFZVJysIX5WUk+fc7RKCs5ho0ldYen4w82d7Lm4xquOzGXmMixs8FBqZHy9yfxc8AXXbe/CKz2OP4F127LE4HGUFs/BrBieT49ZzRiImysWJ7v974syUuhtcvB9n1+WmjudELlJnjj5/D3k+FPc+Ctnx8pRxQWDrM/A5ffC7M/3WswBlBU2Ujx/uagGh0DSI6LZEJC1KhY2P/kpgoOtXSG7OgYQE5KHI3tdhraugY+eRjc60Hdf2A5nIYfPbuNVQW9/h0Z0rJSYmnu7Kax3Q5Yry+7w/D5E4NrBkOpQPNl2ovHgA+AfBGpFJEbgN8AnxKRXcA5ru8BXgL2AruBfwHf8FW/AmnGxAScBhKiwxGsdAi/vnyOX9ePufml0HhXK+x4EVbfDL/Ph3+fDe/+EWKS4Ywfgs2jMoGzG4oeHbBY9xMbK4iJsAVlLc789ISAFxnv6nZyz9o9LM5JDunM6e4i475a2N/betB2u4OVa4p98nyjmXunZWV9Ow6n4dEPyzl5ampI7dxVyh98ucvy6j7uOruXcw3wTV/1ZbT429rdJESF8+4Pzwp4Xp70xGiyUqyphhtOzfNew03VRwp2l6yD7g6IGmclZ82/AKadDbEpVrFuesw4D1Csu7Wzm+cKq7hgzqSgLE0za9I4Hny/NHDTxFgjO9WNHfzy8jmjZrenL+S4Ul+U1rYyzwfTiKNlPehokOlODlvXxv6mDqoa2rnjwlkB7pVSwUcz9fvJ7gMtvLR1HzedMTXgwZjbktwU1hUfHFkqBmNgX5ErCHvJug3WIvxF10P+eZB9MoRHHv24YaSneHHrPlq7HHxuaXBNV7rlT0ygq9tJaW0r0yYk+P35ux1O/r52N8dnjGNZgNex+Zo7OWy5j0bIJo6Lpqap45jjgVgPGmju5LAV9W18sKeWCQlRnHNccFcBUSoQNCDzk3+s3UNUeJh3R6NGaGluCs9sqWLvodaBpxeaa+Cp6+GKB63F9yVvW6WKdq6BpipAIGspnP1TayRsfH7/Bbs901OsXQvLlg3Y3yc3VjBlfByLR1n5ocHKdy3s31HTHJCA7MWt+yitbeOeaxeG9OgYQEykjYnjonySrb+ls/uYtaAQuPWggZYYE0FCdDgf7Kll7c6DfOus6UQEaARYqWCmAZkfVNS1saqwii+elEtqfNTAD/CTJXnWGqKNJXUDB2Sv/wzKPoD7PgWtB8HeBhFxMO0sOPPHMP1ciPfdqMvuA81sKqvnRxfMDNpgYtqEeGxhQnFNMxf5OT2T02n4+1t7mD4hnnOPS/fvkwdITmoc5XXeTX1hdzi56eHN7G/u5GtnTOGFon1Ii7UedMXy/ICsBw20VQVVtHc5eKv4IAApcaNjBkCpYKMBmR/cs24PNhFuPH1KoLtylClpcaTGRbKhtI7PLe2xI8oYOPCJlSV/+3NHpiIbymD+NdaOyNxTIcI/ObWe2FhBeJgEdZHi6AgbuamxAdlp+dr2/RTvb+aPV80jbIwkL81JiWXtzoNea88Yw4+f3co7uw7x28/M4aol2dx+/izWrg1j2SBGeEORe7dpt/PIetDfvlxMUkzkmAxOlRoJDch8bH9TB//bVMkVizNJTwx8QlBPIsLi3OQjCWK7u6DsXWtB/s6XrVxhALGpIDarbJEtEsJjYPo5futnV7eTp7dUcc6siaSNohHG4ZiZPo6tVY1+fU5jDH97azfZKbFjKlFnblocBzdX0tbVTWzkyH/V/eXN3Ty5qZJvnzWNq5ZoSgfof7epBmRKDY1O9PvYvW/vxWEMN50xNdBd6dWpGWEsbniV9keug5VT4b+fhi3/sUoVXfQnuPFtK32Fcf3SdXRB4SMDpqfwpje276eutYurgnQxv6f89ATK69po7ez223OW1bXxUWUjNy2bGrDdnYHgXtjvjdQXT22u5A+v7eTyhRl851MzRtxeqNDdpkp5j46Q+VBdaxePfljOpfMnH96JNCoc2mXtiCx+hWsr1nNdpJOO8jSYfZm1ID/vDIh09feF7x5J3uo2QHoKb3t8YwWTEqM5fXrw7wx0L+zfub/Z51nyj2SSryJMMogYI1OVbrmu1BdltW0jqurw7q5D3Pb0R5wyLZXfXD43aNcw+sJoqj6iVLDTgMyH7n+3hI5uB99Y5seM6J67IRNcW88d3VCx3loPVvwy1O2xjk+cgznlu1z9djIzZp7O/13Sy0rzYaSn8Kaqhnbe3nWQb505LSQKNx8poeTbgMy9tqfd7mB8ODgN/L/VHxNuCxszU0nZh5PDDn9h//Z9TXz94c1MHR/PP65dRGT42BlhHIwVy/MPv87cxupuU6VGSgMyH2lst/Of90u54PhJTJvgx4zV6+6C8vXw5s9h6pnWerBdr0JHg1WwO+90OPEmq2B3UjZhQETZh2woa+i9Pc/0FAHw1KZKAK5cHPzTlQBZybHERtp8vrBf1/ZY6RiSYyMoqxvelOW+xnauf2Aj8VHhPHD9EsYFYTJiX3O/llauKaa6oZ3JY3i3qVIjpQGZj/z3g1KaO7v5xpl+XDtWscFa/2WcUPBf6ysmxZqGzD8Ppp4FUcfmv1qSm8IfX99JY5udxNjR86HjcBqe3FTBKVPTRteU7wiEhQnTJ/q+hJKu7bHkpMYNa4SsqcPO9Q9spKWzmye/dpJOwfXjsgUZGoAp5QUakPlAa2c3971bwlkzJzB7cqLvnsjpsAp273zZGgk7uP3IfRJmBWKffQjCbP02syQ3BWNgU1kdZ88aPRm239t9iKqGdm47f2agu+JVMycm8Nr2/SOrkDCAlLhIaluPLaw91gKLnNRYNpXWD+kxdoeTbzy8hd0HWrj/S0s4bvLw158ppdRg6YIIH3hsQzn1bXa+eaYP1o51tsAnz8Gqb8DvZsD958J7f7bqRYZ5xNfGCbtfh9ZDAza5IDuJCJv4ttD4MDyxsYKk2AjOnT16gkRvyE9PoK61i4MtnT5pv7y2jbaubnqGemNxbU9Oahz7Gtvp7HYMfDJWipDbnt7Ku7sP8evL53B6iJeYUkqNHhqQeVmH3cG9b+/l5KmpLPJWiZ/GStj4b3j4M3BXHjx5Hex4AaYsg8/cBz/YA+nHW6Ninty7IQcQHWFjTkYiG0tGT0BW19rFq5/UcPmCTKLC+x/hCzbuhf079nl/2rK9y8HXH95MhC2MH184i4ykGAQrk/yvL58z5qaWclJicRqorB/cVO2fXt/F01squfWc6SGzblEpFRx0ytLL/re5kgPNnfzpc/OH34jTCfsKjxTsrtlqHU/OgyVfdRXsPglsHuu9RrgbckleirUr1O4gOiLwAdAzWyqxOwxXLQm9D8V8j52W3hyBcWeS317TxP1fXMKZMyfwldOmjOlM8rlpR4qMD1Qe7MlNFdz9xi6uWJTJLWdP90f3lFLqMA3IvMjucHLP2j0szE7ipCmpfZ/YW2oKezvsXXdkPVhLjTXilXUCnPMzyD8f0mb0XbB7hLshl+am8M91eymsaODE/vruB8YYnthYwfyspMPBSyhJjY9ifEKU13da/nd9Gc8UVPGdc2Zw5swJXm07WGWnWLnISgdY2P/2zoP86JmtnDY9jV9fPkdzjSml/E4DMi9aVVBFVUM7P79sdv+/0N2pKV6/E7JPtEbC9rwF3e0QGQ/TzoYZ51sFu+P8ExwtzklBxCo0HuiArKCigV0HWvjN5XMC2g9fmpmeQPH+Jq+1t6m0jv97/hPOnjmBb53lx7x3o1xafCRxkbZ+s/V/Ut3ENx7ZwrQJ8fz98wuJGEPVDJRSo4cGZF7icBr+sXYPx00ax5n5fYxOGGONgrlTUxQ9an0lZsGCa61RsNxTIdz/9RoTYyPIn5gwKhb2P7GhgthIGxfNC926i/kTE/jv+jIcTjPihLcHmjv4xiNbyEiO4Q9XzR8zxcMHQ0TI7if1RXVDO9c/uIGE6HAevH4pCZprTCkVIBqQecnL2/ax91Arf//8wqNHx7o7ofQdV8HuV6Cx4sh9YoPjLoErHuh7KtKPluSm8MyWSrodzoDVPGzp7Ob5j6q5aO4k4qNC9+WZn55AZ7eT0trWAdc29cfucPLNR7bQ3NHNQzcsJTFGA4qeclNjKd5/7PSwO9dYW6eD/910EumJ0QHonVJKWXRs3guMMfz1zd1MHR/HebPTobUWCh+FJ66Du6ZYuyMLHoa06Va2/MMPdFiljFoOBK7zHpbkpdDa5WC7D3b/DdYLRdW0dTm4akl2wPrgDzPTrdxWI00Q+8sXt7OxtJ7ffGbO4TbV0bJTY6moa8PhNIePdXU7uenhzew52MI91y3Sa6eUCjgNyLzgjU/2Y9+/g7sz1xL2wHnwu2mw6iao3AhzroCrn4Aflli7JHuOhA0yNYU/LMm10nQEctryiU0VTJ8Qz8LspID1wR+mT4wnTBjRwv5VBVU8+H4pXz4lj0vnj610FkORmxqH3WHY12ilvrByjX3Ee7tr+e1n5nLKtLQA91AppXTKcvgcdij/ALPjJWZvXMUbUftgO5A+F05fYa0HS58HYR4xb4ALdQ9kUmIMmckxbCyp44ZT8/z+/MU1zRSUN3DHhbNCfpdbdISN3NQ4imuGt7D/k+ombnvmI5bmpXD7BaFVycDbclLcRcbbyEyO5Y+v7eSZgiq++6kZfGZRZoB7p5RSFg3I+tNcAwWPwKJZVnqK9nrY/YaVG2z369DRiAmLZId9FhVzbmDp8qshsZ9f8AEu1D0YS3NTWLfzoE/L+vTliY0VRNiET4+R5KX56Qls3zf0gKyxzc7XH95MYkwEf7tGdwUOxL1+7PP//pCkmAga2u1ctThLd6MqpUYVDcj6s+4uaxH+k9eBLRLK3rfWfcWmwcyLIf88rl8XR3GdYd3lyyAEMsovyUvhmYIq9h4a2WLzoersdvBsQSXnHpdOarz/d5kGQn56Aq98XENbVzexkYN7KzqdhlufKGBfYzuP33gS4xPGxrUarlUFVdz1yo7D3ze02wkTWJqXHPKjsEqp4KJ/WveluQa2PGTdrvgQmvfDKbfADa/B93fCZX9jU8wprCtt56unTwmZ8j5LclMA/F5G6bVP9lPfZuezIZiZvy8z0xMwBnbtbxn0Y+5+YxdvFR/kJxfP9l5prhC2ck0x7XbnUcecBv7w2q4A9UgppXqnAVlf1t3F4erMYRGQdxqc81PIWgphVvD117d2kxoXydVLQyeImDo+jtS4SL8v7H9iYwUZSTGcOoYWWOcPcaflG9v3c/cbu/jMwkyuPSG0d6F6S3VD7zUs+zqulFKBogFZb5proPARa+E+gNNufd+8//ApWysbWVt8kC+fmjfo6aZgICIszk1mox8DssZ2O+/sOsSVizNHnCQ1mGSnxBIdEcb2QSzsLz3Uyq1PFDJ78jh++enjdbptkCYnxQzpuFJKBYoGZL1Zd5eVjsJTj/QUf3trN+Oiw/nCSTl+7pzvLclNoaKunZrGDr883yfVTYjAlYtDZ6RxMGxhwoyJCQOOkLV1dfO1/27GFibcc+2iUVH8PVisWJ5PTI/rFRNhY8Xy/AD1SCmleqcBWW8GSE+xc38zr3xcw5dOzg3JUitL86x1ZP6YtnQ4DZ9UN3La9PFkjMFRi5np/QdkVs6srew80MyfP7eALFcKBzU4ly3I4NeXzyEjKQYBMpJi+PXlc7hsjOzkVUoFj9CZa/Mmz/QUa9fCsmVH3f33t3YTG2nj+lP8n6vLH46bNI64SBsbS+q4xIf1JFcVVPHzFz4hq7Ob8soGVhVUjbkPyvz0cTy5qZKDzZ297pi8/71SniuqZsXyfE6fMT4APQx+ly3IGHOvK6VU8NERsiEqq23luaJqrj0xh+S4yEB3xyfCbWEszPHtOrJVBVXc/sxWalutkci6Nju3P7OVVQVVPnvO0WhmegLQ+8L+9Xtr+dVL2zn3uIncdMZUf3dNKaWUH2lANkT/WLuHcFsYXwlAJnt/WpKbQvH+Zhrb7D5p/641O2i3O4461m53sHJNsU+eb7TKdwVkO3os7K9p7ODmR7eQkxLL7z87j7AxtNlBKaXGIg3IhqC6oZ2nt1TyuSVZTBgXHeju+NSS3BSMgc3l3h8lK6xooLqh9w0DYy0dQVp8FGnxkUeNkHV1O7npkc20dTn453WLQnKdolJKqaNpQDYE9769F2Pga2Ng+mhBdhIRNmFDSb3X2mzqsPOT1dv49N/fo68Bn7GYjiA/PeFweR+An7/wCQXlDay8Yh7TJyYEsGdKKaX8RQOyQTrY3MljG8r59IKMMbEbMDrCxpyMRK+sIzPG8OJH+zjn9+t4eH0ZXzwpl199+nhNR+CSP3EcO/c343AantpcyX/Xl/G106dw4dxJge6aUkopP9FdloN037sl2B1ObloW+qNjbkvyUrj/3RI67I5h576qqGvj/63extrigxyfMY5/f3ExczOTAIiOCGflmmKkxUpHsGJ5/pjcDdfW1U2H3cnUH70EwLTxcWMyMFVKqbFMA7JBaGjr4r8flHLh3MlM8WPB7UBbkpPCP9ftpbCigROnpA7psXaHk3+9s5c/v7ELmwg/ueg4vnBSDuG2I4Oy7nQEa9eGsaxHapGxYlVBFc/22Fla2dDOCx/tG5PBqVJKjVUakA3Cg++X0trl4Jtnjp3RMYDFuVbx6o0ldUMKyDaX1fGjZ7ZRvL+Z5bMncucls5mUGPrTvMOxck0xnd1HV4XosDtZuaZYAzKllBpDNCDrw6qCKlauKWZCy24KHa0cP3kcM13FoMeKpNhI8icmDDpjf0NbF799ZQePbbAKhf/7C4s557iJPu5lcNPi10oppUADsl65k5a22x2MDwdjYNeBljGZSX5JXjLPbqmi2+E8arrRkzGG1YXV/PyFT2hot3Pj6VO45ezpxEXpy2sgk5NiqOol+BqLu02VUmos012WvVi5pviYpKWd3c4xl7QUrHxkrV0Otu/rvd5iyaFWrrtvA7c+UUhWSizP33wqP7pglgZjg6TFr5VSSoGOkPVKp5GO8Cw0Picz8fDxzm4H/1y3l7++tZsoWxg/v3Q215yQg00zyg+Je8R15ZpiqhvamTyGd5sqpdRYpgFZL3Qa6YhJiTEkx0awcs0OfvHCJ0xOiuHTCybz0rYa9h5s5aK5k/jJRceFfOUCX9Li10oppXTKshc6jXTEqoIqmtqtPFkGqGpo569v7aGhrYsHr1/CX69ZqMGYUkopNUI6QtYLz2mksZ60dOWaYhzGHHM8OtzGsvwJAeiRUkopFXo0IOuDJi219LVubl9j78XBlVJKKTV0OmWp+tXXurmxuJ5OKaWU8hUNyFS/dD2dUkop5Xs6Zan6pWkZlFJKKd8bVQGZiJwH3A3YgH8bY34T4C4pNC2DUkop5WujZspSRGzA34DzgeOAq0XkuMD2SimllFLK90ZNQAYsBXYbY/YaY7qAx4FLA9wnpZRSSimfG00BWQZQ4fF9peuYUkoppVRIG00B2aCIyI0isklENh08eDDQ3VFKKaWUGrHRFJBVAVke32e6jh3FGHOvMWaxMWbx+PHj/dY5pZRSSilfGU0B2UZguojkiUgk8DnguQD3SSmllFLK50ZN2gtjTLeI3AyswUp7cb8x5uMAd0sppZRSyudGTUAGYIx5CXgp0P1QSimllPInMcYEug/DJiIHgTIfP00acCiI2vVl29qutqvtarvabmi168u2td1j5Rhjel0AH9QBmT+IyCZjzOJgadeXbWu72q62q+1qu6HVri/b1naHZjQt6ldKKaWUGpM0IFNKKaWUCjANyAZ2b5C168u2tV1tV9vVdrXd0GrXl21ru0Oga8iUUkoppQJMR8iUUkoppQJMA7J+iMh5IlIsIrtF5DYvtXm/iBwQkW3eaM+j3SwReUtEPhGRj0XkFi+1Gy0iG0SkyNXuz7zRrkf7NhEpEJEXvNhmqYhsFZFCEdnkxXaTROQpEdkhIttF5CQvtJnv6qf7q0lEbvVCdxGR77j+z7aJyGMiEu2ldm9xtfnxSPva2/tBRFJE5DUR2eX6N9lL7V7p6rNTRIa1k6qPdle6XhMficizIpLkpXZ/7mqzUEReFZHJ3mjX477viYgRkTQv9fdOEanyeC1f4K3+isi3XNf4YxG5y0v9fcKjr6UiUuildueLyHr37x8RWeqldueJyAeu323Pi8i4YbTb6+fESN9z/bQ7ovdcP+2O6D3XT7sjfs+NiDFGv3r5wqoWsAeYAkQCRcBxXmj3dGAhsM3L/Z0ELHTdTgB2eqm/AsS7bkcAHwInerHf3wUeBV7wYpulQJoPXhP/Ab7iuh0JJHm5fRtQg5WnZqRtZQAlQIzr+yeBL3mh3eOBbUAsVmLp14FpI2jvmPcDcBdwm+v2bcBvvdTuLCAfWAss9mJ/zwXCXbd/68X+jvO4/W3gHm+06zqehVUVpWw475U++nsn8P0Rvr56a/dM1+ssyvX9BG9dB4/7fw/8xEv9fRU433X7AmCtl9rdCJzhuv1l4OfDaLfXz4mRvuf6aXdE77l+2h3Re66fdkf8nhvJl46Q9W0psNsYs9cY0wU8Dlw60kaNMW8DdSNtp5d29xljtrhuNwPbsT6UR9quMca0uL6NcH15ZeGhiGQCFwL/9kZ7viQiiVi/JO8DMMZ0GWMavPw0ZwN7jDHeSnYcDsSISDhWAFXthTZnAR8aY9qMMd3AOuDy4TbWx/vhUqzgF9e/l3mjXWPMdmNM8TC6OVC7r7quBcB6INNL7TZ5fBvHMN53/fy++SPwg+G0OUC7I9JHuzcBvzHGdLrOOeCldgEQEQE+CzzmpXYN4B69SmQY77s+2p0BvO26/RrwmWG029fnxIjec321O9L3XD/tjug910+7I37PjYQGZH3LACo8vq/ECwGOP4hILrAAazTLG+3ZXMP5B4DXjDFeaRf4E9aHgtNL7bkZ4FUR2SwiN3qpzTzgIPCAWFOs/xaROC+17fY5hvGh0BtjTBXwO6Ac2Ac0GmNe9ULT24DTRCRVRGKxRgCyvNCup4nGmH2u2zXARC+370tfBl72VmMi8ksRqQA+D/zES21eClQZY4q80V4PN7umfO4fzlRzH2ZgveY+FJF1IrLES+26nQbsN8bs8lJ7twIrXf9vvwNu91K7H3NkUOBKRvi+6/E54bX3nLc/fwbR7ojecz3b9cV7brA0IAsxIhIPPA3c2iPaHzZjjMMYMx/rr5ClInL8SNsUkYuAA8aYzSNtqxenGmMWAucD3xSR073QZjjWFMI/jDELgFasoX2vEJFI4BLgf15qLxnrl3ceMBmIE5FrR9quMWY71hTBq8ArQCHgGGm7/Tyfwc9/pQ6XiPwY6AYe8VabxpgfG2OyXG3ePNL2XEH0j/DNB80/gKnAfKw/An7vpXbDgRTgRGAF8KRrVMtbrsZLfwi53AR8x/X/9h1co+pe8GXgGyKyGWuarWu4DfX3OTGS95wvPn/6a3ek77ne2vX2e24oNCDrWxVH/wWS6To2aolIBNaL6xFjzDPebt81RfcWcJ4XmjsFuERESrGmg88SkYe90K57dMg9tfEs1vTzSFUClR6jg09hBWjecj6wxRiz30vtnQOUGGMOGmPswDPAyd5o2BhznzFmkTHmdKAea/2FN+0XkUkArn+HPEXlbyLyJeAi4POuDzRve4RhTFH1YipWkF7keu9lAltEJH2kDRtj9rv+eHMC/8I77zuw3nvPuJZPbMAaUR/yRoTeuKbzLwee8EZ7Ll/Eer+B9QeWV66DMWaHMeZcY8wirAByz3Da6eNzYsTvOV99/vTV7kjfc4Por7fec4OmAVnfNgLTRSTPNXrxOeC5APepT66/GO8Dthtj/uDFdse7d7CISAzwKWDHSNs1xtxujMk0xuRiXds3jTEjHsERkTgRSXDfxlr8OeIdrcaYGqBCRPJdh84GPhlpux68/Vd6OXCiiMS6XhtnY62TGDERmeD6Nxvrw+xRb7Tr4TmsDzVc/672cvteJSLnYU29X2KMafNiu9M9vr0U77zvthpjJhhjcl3vvUqsxc01I23b/YHu8mm88L5zWYW1sB8RmYG1ocZbBaDPAXYYYyq91B5Ya8bOcN0+C/DKVKjH+y4MuAO4Zxht9PU5MaL3nA8/f3ptd6TvuX7a9fp7bkiMH3cQBNsX1vqYnVh/ifzYS20+hjWcb8f6ZXiDl9o9FWuY+SOsaaRC4AIvtDsXKHC1u41h7EQaxHMsw0u7LLF2xRa5vj721v+bq+35wCbXtVgFJHup3TigFkj08nX9GdYvlG3Af3HtUvNCu+9gBaNFwNkjbOuY9wOQCryB9UH2OpDipXY/7brdCewH1nip3d1Y603d77vh7Ibsrd2nXf93HwHPYy06HnG7Pe4vZXi7LHvr73+Bra7+PgdM8lK7kcDDrmuxBTjLW9cBeBD4updfv6cCm13vjw+BRV5q9xasz6OdwG9wJXYfYru9fk6M9D3XT7sjes/10+6I3nP9tDvi99xIvjRTv1JKKaVUgOmUpVJKKaVUgGlAppRSSikVYBqQKaWUUkoFmAZkSimllFIBpgGZUkoppVSAaUCmlApqIpIrIt7KedVb+z8a4ePXishib/VHKRWaNCBTSqleiCUMq9SQUkr5lAZkSqmQISJTXMXfXxSRua5jBSLyE9ft/xORr4pIvIi8ISJbRGSrq+C2e7StWEQewkoQeR8QIyKFIvKI65xVrsL1H3sWrxeRf4jIJtfxn/n9h1dKBbXwQHdAKaW8wVXW6nHgS1i1QU8TkTKs4sOnuE47Dfg60AF82hjTJCJpwHoRcZdGmw580Riz3tXulcaY+R5P9WVjTJ2rlNhGEXnaGFOLVRWiTkRswBsiMtcY85FPf2ilVMjQETKlVCgYj1V/7/PGmCKs8k6nYwViLwLxIhIL5BljigEBfiUiH2GViskAJrraKnMHY334togUAeuBLKwADuCzIrIFq9TYbOA4b/6ASqnQpiNkSqlQ0IhVUP1UrDqbG4HFwF7gNSAN+CpWjUGAz2MFcYuMMXYRKQWiXfe19vUkIrIMqyD1ScaYNhFZC0SLSB7wfWCJMaZeRB70aE8ppQakI2RKqVDQhVXI+Asico0xpgur+PCVwAdYI2bfB952nZ8IHHAFY2cCOf20bReRCI/H1buCsZnAia7j47ACuUYRmYg1ZaqUUoOmI2RKqZBgjGkVkYuA10SkBSsIO9sY0y4i7wCZrmMAjwDPi8hWYBOwo5+m7wU+ck1Hfhn4uohsB4qxpi0xxhSJSIGrnQrgvf/fnh2cAADDQAyj+w+dLhEwtNIEl58h+xcCLzszU28AAPialyUAQEyQAQDEBBkAQEyQAQDEBBkAQEyQAQDEBBkAQEyQAQDELlwJlTdJzbK3AAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"plot_trends(opbrengsten, predict_trend(range(24)), sub_title='trend model')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Als we nu de betrouwbaarheid van dit model willen bepalen, passen we de functie toe op het verleden en vergelijken de\n",
"gevonden waarden met de echte waarden:\n",
"\n",
"```python\n",
"forecast_errors(opbrengsten, predict_trend(range(20)), 'trend model')\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>MAE</th>\n",
" <th>RMSE</th>\n",
" <th>MAPE</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>trend model</th>\n",
" <td>85.0</td>\n",
" <td>100.616689</td>\n",
" <td>1.149211</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" MAE RMSE MAPE\n",
"trend model 85.0 100.616689 1.149211"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"forecast_errors(opbrengsten, predict_trend(range(20)), 'trend model')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Merk op dat de RMSE exact gelijk is aan de standaardschattingsfout ($s_{e}$) van de regressie (kijk zelf maar na). De\n",
"berekening is namelijk dezelfde.\n",
"\n",
"Bemerk dat je de MAE, RMSE en MAPE ook zou kunnen berekenen door het model steeds opnieuw op te stellen voor opeenvolgende waarden (zoals hierboven werd gedaan). We kiezen in dit document echter om het berekende model te gebruiken in het verleden omdat we niet verwachten dat dit model veel zal veranderen naarmate er meer data beschikbaar\n",
"komt. Als dit toch het geval is, moet je dus steeds een nieuw model opstellen, naarmate er meer data beschikbaar is.\n",
"\n",
"Dit model is niet zo heel goed. De voorspelde waarden volgen een rechte lijn, terwijl de echte waarden steeds meer schommelen rond die lijn. Daardoor wordt de fout ook steeds groter. Dit model kan die variaties niet goed voorspellen en\n",
"is enkel bruikbaar als de oorspronkelijke data gelijkmatiger verandert. Als we ook de schommelingen willen meenemen, hebben we nood aan een ander model. Dit bespreken we hieronder.\n",
"\n",
"## Seasonal forecasting\n",
"\n",
"### Het principe\n",
"\n",
"Bij seasonal forecasting gaan we ongeveer op dezelfde manier te werk als bij regressie. We zoeken namelijk een soort formule (een model) waarmee we voorspellingen kunnen doen. We gebruiken alleen geen lijn, maar een ander model.\n",
"\n",
"Tijdsgebonden data bestaat namelijk meestal uit een aantal componenten:\n",
"\n",
"- een (al dan niet lineaire) trend (stijgend of dalend)\n",
"- een seizoensgebonden trend (een patroon dat om de zoveel metingen steeds terug komt)\n",
"- een niet regelmatige component (we beschouwen dit als ruis die niet te voorspellen is)\n",
"\n",
"We kunnen er nu vanuit gaan dat elk datapunt gelijk is aan de som van deze componenten. We krijgen dus:\n",
"\n",
"$$data = trend + seizoen + ruis$$\n",
"\n",
"Of meer wiskundig:\n",
"\n",
"$$x_{i}=T(i)+S(i)+R(i)$$\n",
"\n",
"Dit noemt men een **additief decompositiemodel**.\n",
"\n",
"Dikwijls worden de seizoensschommelingen groter als de waarden zelf groter worden. Je kan dit zien in het voorbeeld van de opbrengsten: als de opbrengsten groter worden, dan worden de schommelingen ook groter. In dat geval gebruik je beter het **multiplicatief decompositiemodel**. Dit ziet er als volgt uit:\n",
"\n",
"$$x_{i}=T(i)\\cdot S(i)\\cdot R(i)$$\n",
"\n",
"We zijn het meest geïnteresseerd in de formules voor $T(i)$ en $S(i)$ aangezien $R(i)$ niet te voorspellen is. We kunnen\n",
"$T(i)$ en $S(i)$ dan gebruiken om voorspellingen te maken.\n",
"\n",
"### Het bepalen van de seizoensgrootte\n",
"\n",
"Om de formules voor $T(i)$ en $S(i)$ te vinden, moeten we weten hoe groot een seizoen is (de grootte van het wederkerend\n",
"patroon). In vele gevallen is dit al bekend. In ons voorbeeld hebben we de cijfers per kwartaal genoteerd. We verwachten\n",
"dus een patroon dat zich ieder jaar, en dus iedere 4 kwartalen, herhaalt. Dat is ook heel duidelijk zichtbaar in de\n",
"grafiek.\n",
"\n",
"Als je niet weet wat de grootte van een seizoen is, dan kan je dit soms wel vinden via \"autocorrelatie\". We gaan het\n",
"signaal (de gemeten data) correleren met zichzelf, maar dan verplaatst in de tijd. Als we het signaal verplaatsen over\n",
"dezelfde afstand als een seizoen, dan zal de correlatie hoger zijn. We gaan als volgt te werk:\n",
"\n",
"```python\n",
"fig, ax = plt.subplots(figsize=(10, 5))\n",
"lags, acfs, _, _ = ax.acorr(opbrengsten)\n",
"ax.set_xticks(range(-10, 11))\n",
"ax.set_xlabel('offset')\n",
"ax.set_ylabel('correlatie')\n",
"ax.set_title('Auto-correlation opbrengsten')\n",
"```\n",
"Deze plot een grafiek met alle autocorrelatie waarden. De grafiek van de autocorrelaties ziet er in ons voorbeeld als volgt uit:"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"fig, ax = plt.subplots(figsize=(10, 5))\n",
"lags, acfs, _, _ = ax.acorr(opbrengsten)\n",
"_ = ax.set_xticks(range(-10, 11))\n",
"_ = ax.set_xlabel('offset')\n",
"_ = ax.set_ylabel('correlatie')\n",
"_ = ax.set_title('Auto-correlation opbrengsten')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Er is een duidelijke piek bij $i=0$, maar dat is normaal want de waarden correleren nl. perfect met zichzelf. Er is echter ook een piek voor $i=4$ en $i=-4$. Dat wil zeggen dat het signaal, verschoven over 4 tijdseenheden naar voor of achter, sterk lijkt op het oorspronkelijke signaal. De periode van een seizoen is dus 4. Autocorrelatie werkt niet altijd even goed, dus zal je in veel gevallen handmatig moeten bepalen wat de seizoensgrootte is. Gelukkig is dit in de praktijk meestal wel eenvoudig te bepalen.\n",
"\n",
"Je kan de periode dus afleiden uit de autocorrelatie grafiek, maar we kunnen hem ook vinden door alle correlaties te laten berekenen met een Numpy functie en vervolgens op zoek te gaan naar de 2e hoogste waarden (de hoogste waarde komt overeen met een verschuiving 0).\n",
"\n",
"\n",
"```python\n",
"def find_period(y: np.array, maxlags=10, top_n=1) -> int:\n",
" # autocorrelatie aan beide zijden\n",
" acfs = np.correlate(y, y, mode='full') / np.sum(y ** 2)\n",
" # midden bepalen\n",
" middle = acfs.size // 2\n",
" # omgekeerde argsort vanaf (midden + 1) tot maxlags + top selectie\n",
" return (np.argsort(-1 * acfs[middle + 1: middle + maxlags]) + 1)[:top_n]\n",
"\n",
"m = find_period(opbrengsten)\n",
"m # m is de periode\n",
"```\n",
"We vinden dus een periode van $m=4$."
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"m = [4]\n"
]
}
],
"source": [
"# NO CODE\n",
"m = find_period(opbrengsten)\n",
"print('m =', m)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Je kon dit ook vinden uit de acfs die matplotlib `ax.acorr` - functie teruggeeft.\n",
"\n",
"### Het bepalen van de trend\n",
"\n",
"Om de waarden van $T(i)$ en $S(i)$ te vinden, zijn er verschillende technieken.\n",
"\n",
"Meestal begint men met het zoeken van $T(i)$. Dit is de trend in de grafiek, zonder de ruis en zonder het weerkerend\n",
"patroon. We kunnen deze trend gemakkelijk vinden omdat volgende eigenschappen gelden:\n",
"\n",
"- seizoenen hebben een hogere frequentie dan de trend\n",
"- de ruis heeft een nog hogere frequentie\n",
"\n",
"Als we dus de hoge frequenties wegfilteren, dan vinden we de waarden van de trend. Dit kunnen we doen door het voortschrijdend gemiddelde te nemen van steeds $m$ getallen (waarbij $m$ de seizoensgrootte is). Als je het gemiddelde\n",
"neemt van $m$ getallen waarbij $m$ de grootte van een seizoen is, dan filter je alle seizoenen en de ruis weg.\n",
"\n",
"In Python zullen we 2 functies maken om dit te faciliteren:\n",
"\n",
"```python\n",
"def smooth(y: np.array, m: int):\n",
" result = np.empty(0)\n",
" for i in range(y.size - m + 1):\n",
" result = np.append(result, [np.mean(y[i:i + m])])\n",
"\n",
" return result\n",
"```\n",
"\n",
"```python\n",
"def find_trend(y: np.array, m: int):\n",
" result = smooth(y, m)\n",
" nan = [np.nan] * int(m / 2)\n",
" if m % 2 == 0:\n",
" result = smooth(result, 2)\n",
" result = np.hstack([nan, result, nan])\n",
"\n",
" return result\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"De functie `smooth()` zal het voortschrijdend gemiddelde berekenen van een reeks getallen. Dat levert een nieuwe reeks op met $n-m+1$ waarden (je hebt namelijk minstens $m$ waarden nodig om te kunnen starten).\n",
"\n",
"We willen de nieuwe waarden echter terug uitlijnen met de oorspronkelijke waarden. We zoeken dus de index waarmee we ieder gemiddelde mee associeren. Als m oneven is, is dat niet zo moeilijk. Stel dat $m=3$, dan zal het eerst gevonden gemiddelde (het gemiddelde van waarden 0, 1 en 2) op index 1 worden geplaatst. Maar als m even is, komt dat niet uit.\n",
"\n",
"Het eerst gevonden gemiddelde moet dan op index 1.5 komen (als $m=4$). Om dat op te lossen wordt het resultaat terug gefilterd, maar nu per 2 waarden.\n",
"\n",
"Het resultaat is als volgt:\n",
"\n",
"```python\n",
"trend = find_trend(opbrengsten, 4)\n",
"trend\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"array([ nan, nan, 79.125, 85.75 , 99. , 109.375, 115.75 ,\n",
" 122.875, 135.375, 148.25 , 153.125, 161.125, 174.25 , 185.75 ,\n",
" 200.5 , 221. , 238.625, 258.625, nan, nan])"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"trend = find_trend(opbrengsten, 4)\n",
"trend\n",
"plot_trends(opbrengsten, trend, sub_title='Trendcomponent zoeken', label2='T(i)')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Er worden op deze manier altijd $\\lfloor m/2\\rfloor$ nan-waarden aan beide zijden toegevoegd.\n",
"\n",
"Nu we de waarden van $T(i)$ kennen, kunnen we verder gaan met het zoeken naar $S(i)$. Het verschil (of het quotiënt als we de multiplicatieve vorm gebruiken) tussen het gefilterde signaal en het originele signaal levert dus een signaal waar enkel nog de oscillaties van de seizoenen en de ruis in zitten. We doen dus:\n",
"\n",
"- $S(i)+R(i)=x_{i}-T(i)$ (additief)\n",
"\n",
"- $S(i)\\cdot R(i)=x_{i}/T(i)$ (multiplicatief)\n",
"\n",
"### Het bepalen van het seizoen\n",
"\n",
"Uit dit signaal (zonder de trend) willen we het patroon (het seizoen) halen dat steeds weerkeert, nl. $S(i)$. Aangezien we de seizoensgrootte kennen, gaan we als volgt te werk: we delen het signaal op in $m$ groepjes met punten die steeds $m$-stappen van elkaar liggen. Dan nemen we de gemiddelde waarde van ieder groepje. Zo vinden we $m$ waarden die een patroon vormen dat gemiddeld voorkomt in het signaal. Dit is $S(t)$. Je ziet dit proces hier grafisch (we nemen het gemiddelde van iedere groep):"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"from scripts.cursus import plot_seizoenen\n",
"\n",
"seizoen_ruis = opbrengsten / trend # multiplicatief\n",
"\n",
"plot_seizoenen(seizoen_ruis)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"In Python kan je het seizoen met de volgende functie vinden:\n",
"\n",
"```python\n",
"import numpy as np\n",
"\n",
"def find_seasons(y: np.array, m: int, method='additive'):\n",
" if method == 'multiplicative':\n",
" seizoen_ruis = y / find_trend(y, m)\n",
" else:\n",
" seizoen_ruis = y - find_trend(y, m)\n",
"\n",
" n = seizoen_ruis.size\n",
"\n",
" seizoens_patroon = np.empty(0)\n",
" # m groepjes middellen die telkens m stappen uit elkaar liggen\n",
" for i in range(m):\n",
" seizoens_patroon = np.append(seizoens_patroon, np.nanmean(seizoen_ruis[np.arange(i, n, m)]))\n",
"\n",
" # patroon herhalen over volledige periode\n",
" return np.tile(seizoens_patroon, n // m) # n // m is het aantal seizoenen.\n",
"```\n",
"\n",
"Met `tile` functie herhalen we het gevonden seizoenspatroon 5 maal (n // m) waardoor we het volgende resultaat krijgen.\n",
"```python\n",
"seizoenen = find_seasons(opbrengsten, 4, method='multiplicative')\n",
"seizoenen.reshape(-1,4)\n",
"```\n",
"Herken je het patroon?"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"array([[0.54832249, 1.11670619, 2.09312815, 0.25803668],\n",
" [0.54832249, 1.11670619, 2.09312815, 0.25803668],\n",
" [0.54832249, 1.11670619, 2.09312815, 0.25803668],\n",
" [0.54832249, 1.11670619, 2.09312815, 0.25803668],\n",
" [0.54832249, 1.11670619, 2.09312815, 0.25803668]])"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"seizoenen = find_seasons(opbrengsten, 4, method='multiplicative')\n",
"seizoenen.reshape(-1, 4)\n",
"plot_trends(seizoenen, sub_title='Seizoenscomponent', label1='S(i)', color='green')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"### Het bepalen van de ruis\n",
"\n",
"Nu we ook de waarden van het patroon hebben, kunnen we de ruis bepalen:\n",
"\n",
"- $R(i)=x_{i}-T(i)-S(i)$ (additief)\n",
"\n",
"- $R(i)=x_{i} / T(i) / S(i)$ (multiplicatief)\n",
"\n",
"In ons multiplicatief voorbeeld doen we dus:\n",
"\n",
"```python\n",
"ruis = opbrengsten / trend / seizoenen\n",
"ruis\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"array([ nan, nan, 1.05664355, 0.58752693, 0.68160139,\n",
" 1.11347871, 1.01122842, 0.82002741, 1.01038463, 0.93626345,\n",
" 1.01712816, 1.15450777, 0.96289511, 0.97383106, 0.91499986,\n",
" 1.4379379 , 1.34511887, 0.97642678, nan, nan])"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"ruis = opbrengsten / trend / seizoenen\n",
"ruis\n",
"plot_trends(ruis, label1='R(i)', color='gray', sub_title='Ruiscomponent')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"We hebben nu alle componenten van het signaal ontleed en je kan nagaan of de waarden kloppen door alles weer te vermenigvuldigen (of op te tellen als je additief werkt):\n",
"\n",
"```python\n",
"trend * seizoenen * ruis # moet gelijk zijn aan opbrengsten\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"array([ nan, nan, 175., 13., 37., 136., 245., 26., 75., 155., 326.,\n",
" 48., 92., 202., 384., 82., 176., 282., nan, nan])"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"trend * seizoenen * ruis"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Dit zijn inderdaad de waarden van \"opbrengsten\". Er zijn een paar waarden die we niet terug vinden omdat het\n",
"voortschrijdend gemiddelde pas vanaf waarde 4 (de waarden van $m$) berekend kon worden.\n",
"\n",
"Al deze handelingen zijn nogal **veel werk**. Je kan dit natuurlijk ook in een functie zetten, maar gelukkig hebben een aantal programmeurs dit al gedaan in Python. In de praktijk zullen we deze functie dus gebruiken ipv de berekeningen hierboven.\n",
"\n",
"Je gaat als volgt te werk:\n",
"```python\n",
"from statsmodels.tsa.seasonal import seasonal_decompose\n",
"\n",
"sd_model = seasonal_decompose(opbrengsten, model='multiplicative', period=4)\n",
"\n",
"# de verschillende componenten van het model zitten in trend, seasonal en resid\n",
"sd_model.trend\n",
"sd_model.seasonal.reshape(-1, 4)\n",
"sd_model.resid\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"array([ nan, nan, 79.125, 85.75 , 99. , 109.375, 115.75 ,\n",
" 122.875, 135.375, 148.25 , 153.125, 161.125, 174.25 , 185.75 ,\n",
" 200.5 , 221. , 238.625, 258.625, nan, nan])"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"text/plain": [
"array([[0.54611163, 1.11220357, 2.08468854, 0.25699626],\n",
" [0.54611163, 1.11220357, 2.08468854, 0.25699626],\n",
" [0.54611163, 1.11220357, 2.08468854, 0.25699626],\n",
" [0.54611163, 1.11220357, 2.08468854, 0.25699626],\n",
" [0.54611163, 1.11220357, 2.08468854, 0.25699626]])"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"text/plain": [
"array([ nan, nan, 1.06092125, 0.58990546, 0.68436077,\n",
" 1.11798649, 1.01532226, 0.82334719, 1.01447505, 0.9400538 ,\n",
" 1.02124588, 1.15918165, 0.96679327, 0.9777735 , 0.91870413,\n",
" 1.44375922, 1.35056442, 0.98037972, nan, nan])"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"from statsmodels.tsa.seasonal import seasonal_decompose\n",
"\n",
"sd_model = seasonal_decompose(opbrengsten, model='multiplicative', period=4)\n",
"sd_model.trend\n",
"sd_model.seasonal.reshape(-1, 4)\n",
"sd_model.resid"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"_Behalve de eerste waarde van de ruiscomponenten komt alles overeen met onze eigen berekeningen_.\n",
"\n",
"Om het resultaat te plotten, kan je volgend commando gebruiken:\n",
"```python\n",
"sd_model.plot()\n",
"```\n",
"Als je meer controle wil over de plot, kan je hem ook zelf bouwen:\n",
"```python\n",
"def plot_seasonal_decompositon(sd_model, title: str):\n",
" fig, axes = plt.subplots(nrows=4, ncols=1, figsize=(8, 8))\n",
"\n",
" axes[0].plot(sd_model.observed, 'o-', label='observed')\n",
" axes[0].set_ylabel('observed')\n",
" axes[0].set_title(title)\n",
" axes[0].legend()\n",
"\n",
" axes[1].plot(sd_model.trend, 'o-', color='orange', label='trend')\n",
" axes[1].set_ylabel('trend')\n",
" axes[1].legend()\n",
"\n",
" axes[2].plot(sd_model.seasonal, 'o-', color='green', label='seasonal')\n",
" axes[2].set_ylabel('season')\n",
" axes[2].legend()\n",
"\n",
" axes[3].scatter(range(sd_model.nobs[0]), sd_model.resid, color='darkgrey',\n",
" label='noise')\n",
" axes[3].set_ylabel('residue')\n",
" axes[3].set_xlabel('kwartaal')\n",
" axes[3].legend()\n",
"\n",
"plot_seasonal_decompositon(sd_model, 'Multiplicative')\n",
"```\n",
"In dit geval hebben we ineens een exponentiële regressielijn door de trend berekend en geplot (meer informatie\n",
"hieronder). Het resultaat is als volgt:"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 576x576 with 4 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"plot_seasonal_decompositon(sd_model, 'Multiplicative')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"### Voorspellingen maken met de decompositie componenten\n",
"\n",
"Als we voorspellingen willen maken, dan gaan we de grafiek van de trend verder zetten en het patroon verder herhalen. De ruis kunnen we natuurlijk niet voorspellen, dus laten we deze weg.\n",
"\n",
"Om de trend verder te kunnen zetten, kunnen we een regressie uitvoeren op de trend $T$ zodat we een formule hebben om toekomstige $T(i)$ te kunnen berekenen. Een lineaire regressie levert bijvoorbeeld volgende formule:\n",
"\n",
"$$T(i)=a+b\\cdot i$$\n",
"\n",
"Zoals je hieronder ziet, blijkt in dit geval echter een **exponentiële regressie** de beste match te geven ($R^{2}$ is hier gelijk aan 0.992816, wat zeer hoog is). We vinden de lijn als volgt:"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"```python\n",
"X = np.arange(2, 18) # geen NA-waarde opnemen\n",
"y = sd_model.trend[2:18] # daarom van 2 tot 18\n",
"\n",
"reg_model = GeneralRegression(exp=True) # ons eigen GeneralRegression klasse\n",
"reg_model.fit(X, y)\n",
"\n",
"print('R² =', reg_model.r2_score)\n",
"print('a =', reg_model.intercept_)\n",
"print('b =', reg_model.coef_)\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"R² = 0.9928163829760805\n",
"a = 4.276010969603498\n",
"b = [0. 0.07495604]\n"
]
}
],
"source": [
"# NO CODE\n",
"X = np.arange(2, 18) # geen NA-waarde opnemen\n",
"y = sd_model.trend[2:18] # daarom van 2 tot 18\n",
"\n",
"reg_model = GeneralRegression(exp=True) # ons eigen GeneralRegression klasse\n",
"reg_model.fit(X, y)\n",
"print('R² =', reg_model.r2_score)\n",
"\n",
"print('a =', reg_model.intercept_)\n",
"print('b =', reg_model.coef_)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"De gevonden functie voor $T(i)$ is dus:\n",
"\n",
"$$T(i)=e^{4,27601+0,074956\\cdot i}$$\n",
"\n",
"Om een voorspelling te doen, gaan we het patroon herhalen en vermenigvuldigen (omdat we multiplicatief werken) met de trend. In Python doe je dit als volgt door gebruik te maken van de `predict`-methode van de `GeneralRegression` klasse in combinatie met het seizoenspatroon van het seasonal decomposition model:\n",
"\n",
"```python\n",
"predictions = reg_model.predict(np.arange(20, 24)) * sd_model.seasonal[0:4]\n",
"```\n",
"Met het regressie model voorspellen we trend 4 kwartalen vooruit, en daarop superponeren we het seizoenspatroon. We kunnen ook hier weer een functie schrijven die deze voorspellingen doet o.b.v. een regressie model en een seasonal decomposition model.\n",
"\n",
"```python\n",
"# voorspellen met behulp van seasonal decomposition componenten\n",
"def seasonal_decomposition_forecast(reg_model: GeneralRegression, sd_model,\n",
" start, end, method='additive', m=None):\n",
" if not m:\n",
" m = find_period(sd_model.observed)\n",
"\n",
" # seizoenen voldoende herhalen tot voorbij 'end'\n",
" seasonal = np.tile(sd_model.seasonal[0:m], end // m + 1)\n",
" if method.startswith('m'):\n",
" return reg_model.predict(np.arange(start, end)) * seasonal[start:end]\n",
" else:\n",
" return reg_model.predict(np.arange(start, end)) + seasonal[start:end]\n",
"\n",
"\n",
"# gebruik\n",
"predictions = seasonal_decomposition_forecast(reg_model, sd_model, 20, 24, method='multiplicative')\n",
"predictions\n",
"```\n",
"We gebruiken de Numpy `tile`-functie om het seizoenspatroon voldoende malen te herhalen."
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"predictions = [175.94999791 386.22921653 780.2881482 103.67967675]\n"
]
}
],
"source": [
"# NO CODE\n",
"predictions = seasonal_decomposition_forecast(reg_model, sd_model, 20, 24, method='multiplicative')\n",
"print('predictions =', predictions)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Ons regressiemodel, `reg_model` houdt automatisch rekening met het exponentieel maken van de output door de resultaten van een lineaire regressie door een exponentiële functie sturen. De voorspelde waarden volgens dit model zie je in deze grafiek:"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"plot_trends(opbrengsten, np.hstack([np.repeat(np.nan, 20), predictions]),\n",
" sub_title='Seasonal decomposition forecasting')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Zoals je ziet, is dit een vrij goede voorspeller. We kunnen nu ook de kwaliteit van deze voorspeller bepalen door er het verleden mee te voorspellen.\n",
"\n",
"```python\n",
"predictions = seasonal_decomposition_forecast(reg_model, sd_model,\n",
" 0, 20, method='multiplicative')\n",
"forecast_errors(opbrengsten, predictions, 'seasonal decomposition')\n",
"```\n",
"We vinden volgende waarden:"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>MAE</th>\n",
" <th>RMSE</th>\n",
" <th>MAPE</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>seasonal decomposition</th>\n",
" <td>24.29068</td>\n",
" <td>41.807111</td>\n",
" <td>0.22919</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" MAE RMSE MAPE\n",
"seasonal decomposition 24.29068 41.807111 0.22919"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"predictions = seasonal_decomposition_forecast(reg_model, sd_model, 0, 20, method='multiplicative')\n",
"plot_trends(opbrengsten, predictions, sub_title='Seasonal decomposition forecasting')\n",
"\n",
"forecast_errors(opbrengsten, predictions, 'seasonal decomposition')"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Deze voorspeller is (in dit geval) dus bijna even goed als de lineaire combinatie, maar eigenlijk is dit niet correct.\n",
"\n",
"Weet je ook waarom? Denk eerst even na alvorens je verder leest.\n",
"\n",
"_De componenten van de seasonal decomposition (trend en seasonal) zijn gevonden o.b.v. de opbrengstgegevens zelf. Het is daarom nogal wiedes dat die goede voorspellingen produceren aangezien ze alle gegevens \"op voorhand\" hebben kunnen \"bestuderen\". Ze konden als het ware in de toekomst kijken. Het enige wat niet het model opgenomen is, is de ruis, en daarom maakt het nog wat fouten. We moeten bovenstaande cijfers dan ook met een grove korrel zout nemen._\n",
"\n",
"## Seasonal trend forecasting\n",
"\n",
"Bij de vorige techniek proberen we eerst de **algemene trend** te bepalen en zetten daarop een patroon. Maar je kan ook direct een trend zoeken in **ieder punt** van het seizoenspatroon. Als de seizoensgrootte bijvoorbeeld gelijk is aan 4, dan kunnen we kijken naar punten 0, 4, 8, 12, ... . Deze punten komen overeen met alle eerste punten van het seizoen (de eerste kwartalen). We kunnen op zoek gaan naar een trend in die punten. Vervolgens kijken we naar punten 1, 5, 9, 13, ... . Daar kunnen we ook een trend in vinden. Zo gaan we door tot we voor ieder punt van het seizoen een trendlijn hebben. De trendlijn kan met regressie worden bepaald.\n",
"\n",
"We zoeken dus $m$ trendlijnen. Voor ieder van die lijnen gebruiken we punten $i+k \\cdot m$ waarbij $i$ het nummer is van de trendlijn ($i\\in\\{0,...,m-1\\}$) en k loopt van 0 tot en met $\\lfloor(n-1-i)/m\\rfloor$. De x-coördinaten die met deze punten overeenkomen zijn gelijk aan $i+k\\cdot m$.\n",
"\n",
"In ons voorbeeld is n=20 en m=4. We zoeken 4 trendlijnen waarbij we volgende punten gebruiken:\n",
"\n",
"- 0, 4, 8, 12, 16 met waarden 20, 37, 75, 92, 176\n",
"- 1, 5, 9, 13, 17 met waarden 100, 136, 155, 202, 282\n",
"- 2, 6, 10, 14, 18 met waarden 175, 245, 326, 384, 445\n",
"- 3, 7, 11, 15, 19 met waarden 13, 26, 48, 82, 181\n",
"\n",
"In Python kunnen we deze waarden als volgt vinden:\n",
"\n",
"```python\n",
"m = 4 # de periode gevonden met autocorrelatie\n",
"\n",
"for i in range(n // m - 1):\n",
" x = np.arange(i, opbrengsten.size, m)\n",
" y = opbrengsten[x]\n",
" print('{} met waarden {}'.format(x,y))\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[ 0 4 8 12 16] met waarden [ 20. 37. 75. 92. 176.]\n",
"[ 1 5 9 13 17] met waarden [100. 136. 155. 202. 282.]\n",
"[ 2 6 10 14 18] met waarden [175. 245. 326. 384. 445.]\n",
"[ 3 7 11 15 19] met waarden [ 13. 26. 48. 82. 181.]\n"
]
}
],
"source": [
"# NO CODE\n",
"m = 4 # de periode gevonden met autocorrelatie\n",
"\n",
"for i in range(n // m - 1):\n",
" x = np.arange(i, opbrengsten.size, m)\n",
" y = opbrengsten[x]\n",
" print('{} met waarden {}'.format(x, y))"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Nu moeten we voor elk van die lijnen de trendlijn vinden. Dit doen we met regressie. We doen dus $m$ keer een regressie en stoppen al deze modellen in een lijst:\n",
"\n",
"```python\n",
"def find_regression_models(z: np.array, m: int, degree=1, exp=False):\n",
" reg_models = []\n",
"\n",
" for i in range(z.size // m - 1):\n",
" x = np.arange(i, opbrengsten.size, m).reshape(-1, 1)\n",
" y = z[x]\n",
" reg_models.append(GeneralRegression(degree, exp))\n",
" reg_models[i].fit(x, y)\n",
"\n",
" return reg_models\n",
"\n",
"# gebruik\n",
"models = find_regression_models(opbrengsten, m=4)\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [],
"source": [
"# NO CODE\n",
"models = find_regression_models(opbrengsten, m=4)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Merk op dat we de GeneralRegression klasse van het vorige hoofdstuk gebruiken. De parameters degree en exp worden ook meegegeven zodat je ook niet-lineaire regressie kan doen. Deze regressielijnen kunnen we dan gebruiken om voorspellingen te maken.\n",
"\n",
"Volgende functie geeft ons het model voor de voorspelling:\n",
"\n",
"```python\n",
"from cursus.scripts import find_regression_models\n",
"\n",
"def create_seasonal_trend_forecast(z: np.array, m: int, degree=1, exp=False):\n",
" reg_models = find_regression_models(z, m, degree, exp)\n",
"\n",
" def forecast_function(x: np.array):\n",
" predictions = np.empty(0)\n",
"\n",
" for i in range(x.size):\n",
" y = reg_models[i % m].predict(x[i].reshape(1, -1))\n",
" predictions = np.append(predictions, y)\n",
"\n",
" return predictions\n",
"\n",
" return forecast_function\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/plain": [
"array([246.6, 362. , 498.2, 279.6])"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# NO CODE\n",
"seasonal_trend_forecast = create_seasonal_trend_forecast(opbrengsten, 4, degree=2)\n",
"seasonal_trend_forecast(np.arange(20, 24))"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"We zullen in dit voorbeeld kwadratische regressie nemen (deze geeft hier goede resultaten, bekijk zelf maar de alternatieven):\n",
"\n",
"```python\n",
"seasonal_trend_forecast = create_seasonal_trend_forecast(opbrengsten, 4, degree=2)\n",
"seasonal_trend_forecast(np.arange(20, 24))\n",
"```\n",
"We hebben nu een functie `seasonal_predictor()` die we kunnen gebruiken om te voorspellen. De voorspelde waarden voor het volgende jaar zijn:"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"predictions = [246.6 362. 498.2 279.6]\n"
]
}
],
"source": [
"# NO CODE\n",
"seasonal_trend_forecast = create_seasonal_trend_forecast(opbrengsten, 4, degree=2)\n",
"predictions = seasonal_trend_forecast(np.arange(20, 24))\n",
"print('predictions = ', predictions)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"We kunnen deze waarden als volgt plotten (we tekenen de regressielijnen erbij om de werking nog eens duidelijk te maken):\n",
"\n",
"```python\n",
"fig, ax = plt.subplots(figsize=(8, 5))\n",
"\n",
"plot_trends(opbrengsten, np.hstack([np.repeat(np.nan, 20), predictions]), sub_title='Seasonal trend forecasting', ax=ax)\n",
"\n",
"reg_models = find_regression_models(opbrengsten, m=4, degree=2)\n",
"\n",
"for i in range(m):\n",
" ax.plot(reg_models[i].predict(np.arange(24).reshape(-1, 1)), color='red', alpha=0.2)\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"fig, ax = plt.subplots(figsize=(8, 5))\n",
"plot_trends(opbrengsten,\n",
" np.hstack([np.repeat(np.nan, 20), predictions]),\n",
" sub_title='Seasonal trend forecasting', ax=ax)\n",
"\n",
"reg_models = find_regression_models(opbrengsten, m=4, degree=2)\n",
"\n",
"for i in range(m):\n",
" _ = ax.plot(reg_models[i].predict(np.arange(24).reshape(-1, 1)), color='red', alpha=0.2)"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Ook kunnen we nu de betrouwbaarheid van deze voorspelling bepalen:"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"pycharm": {
"name": "#%%\n"
},
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>MAE</th>\n",
" <th>RMSE</th>\n",
" <th>MAPE</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>seasonal trend forecasting</th>\n",
" <td>6.188571</td>\n",
" <td>7.526714</td>\n",
" <td>0.090803</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" MAE RMSE MAPE\n",
"seasonal trend forecasting 6.188571 7.526714 0.090803"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# NO CODE\n",
"predictions = seasonal_trend_forecast(np.arange(20))\n",
"plot_trends(opbrengsten, predictions, sub_title='Seasonal trend forecasting')\n",
"forecast_errors(opbrengsten, predictions, 'seasonal trend forecasting')"
]
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"Dit is dus de beste voorspellingsmethode voor deze data, maar wederom moet je dit met een gigantische korreltje zout nemen, want dit model gebruikt nog meer gegevens (5 modellen in totaal) uit het verleden om datzelfde verleden te voorspellen. In Data Science 2 zullen we betere manieren zien om dit soort gegevens te voorspellen wanneer we het zullen hebben over **neurale netwerken** waarbij we rekening zullen houden met de echte voorspellende kracht van het **neurale model**.\n"
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