Python实现CART，并且展示混淆矩阵

# -*- coding: utf-8 -*-"""Created on Tue Sep  5 16:18:15 2017@author: piaodexin"""from sklearn import datasetsfrom sklearn import cross_validationfrom sklearn.tree import DecisionTreeClassifierfrom sklearn import metrics  #可以展示混淆矩阵，data=datasets.load_iris()x=data.datay=data.targetx_train,x_test,y_train,y_test=cross_validation.train_test_split(x,y,test_size=0.25,                                        random_state=0,stratify=y)#确认模型cart=DecisionTreeClassifier()'''DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=None,            max_features=None, max_leaf_nodes=None,            min_impurity_split=1e-07, min_samples_leaf=1,            min_samples_split=2, min_weight_fraction_leaf=0.0,            presort=False, random_state=None, splitter='best')'''#训练模型cart.fit(x_train,y_train)cart.score(x_test,y_test)#展示模型预测结果print(metrics.classification_report(y_test,cart.predict(x_test))) print(metrics.confusion_matrix(y_test,cart.predict(x_test)))'''print(metrics.classification_report(y_test,cart.predict(x_test)))             precision    recall  f1-score   support          0       1.00      1.00      1.00        13          1       0.93      1.00      0.96        13          2       1.00      0.92      0.96        12avg / total       0.98      0.97      0.97        38print(metrics.confusion_matrix(y_test,cart.predict(x_test)))[[13  0  0] [ 0 13  0] [ 0  1 11]]'''