Commit 226c49e3 authored by TheophilePACE's avatar TheophilePACE

regression prete

parent 9ba21c11
...@@ -33,10 +33,16 @@ ...@@ -33,10 +33,16 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 15,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [] "source": [
"import numpy as np \n",
"from sklearn import datasets\n",
"boston = datasets.load_boston()\n",
"X, y = boston.data, boston.target\n",
"feature_names = boston.feature_names"
]
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
...@@ -104,15 +110,20 @@ ...@@ -104,15 +110,20 @@
"metadata": {}, "metadata": {},
"source": [ "source": [
"## Arbre de régression\n", "## Arbre de régression\n",
"![](https://fr.wikipedia.org/wiki/Arbre_de_d%C3%A9cision#/media/File:Arbre_de_decision.jpg)" "![](https://i0.wp.com/freakonometrics.hypotheses.org/files/2015/06/boosting-algo-3.gif?zoom=2&w=456&ssl=1)\n",
"\n",
"Les arbres de régression sont des modèles très puissants, qui divisent l'espace en zone où tout les points ont le même output. On trouvera dans scikit: https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeRegressor.html"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 13,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [] "source": [
"import matplotlib.gridspec as gridspec\n",
"from matplotlib import pyplot as plt"
]
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
......
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