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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Les arbres de décision avec Python/Scikit-learn
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Step1:  Classification
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Step2:  http
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Python Code:
from sklearn import tree
Explanation: Les arbres de décision avec Python/Scikit-learn
http://scikit-learn.org/stable/modules/tree.html
End of explanation
X = [[0, 0], [1, 1]]
Y = [0, 1]
clf = tree.DecisionTreeClassifier()
clf = clf.fit(X, Y)
clf.predict([[2., 2.]])
clf.predict_proba([[2., 2.]])
Explanation: Classification
http://scikit-learn.org/stable/modules/tree.html#classification
End of explanation
X = [[0, 0], [2, 2]]
y = [0.5, 2.5]
clf = tree.DecisionTreeRegressor()
clf = clf.fit(X, y)
clf.predict([[1, 1]])
Explanation: http://scikit-learn.org/stable/auto_examples/tree/plot_iris.html#sphx-glr-auto-examples-tree-plot-iris-py
Regression
http://scikit-learn.org/stable/modules/tree.html#regression
End of explanation
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