Decision Tree

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from sklearn import tree
X = [[0, 0], [1, 1]]
Y = [0, 1]
clf = tree.DecisionTreeClassifier()
clf = clf.fit(X, Y)

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clf.predict([[1, 1]])

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from sklearn.datasets import load_iris
from sklearn import tree
iris=load_iris()

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clf=tree.DecisionTreeClassifier()
clf=clf.fit(iris.data,iris.target)

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dot_data=tree.export_graphviz(clf,out_file=None,
                             feature_names=iris.feature_names,
                            class_names=iris.target_names,
                              filled=True, rounded=True,
                              special_characters=True
                             )
graph=graphviz.Source(dot_data)

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from sklearn.metrics import confusion_matrix
confusion_matrix(iris.target,clf.predict(iris.data))