机器学习4-评分

直接贴代码

# coding=utf-8from sklearn.datasets import load_iris# 获取鸢尾数据iris = load_iris()X = iris.datay = iris.target# 评分公式from sklearn.metrics import accuracy_score# cross_validation 改成 model_selection# 前者好像是版本问题，过期了from sklearn.model_selection import train_test_splitX_train,X_test,y_train,y_test = train_test_split(X,y,test_size=.3)# 决策树测试# 成功率在90%+from sklearn import treeclf = tree.DecisionTreeClassifier()clf.fit(X_train,y_train)predictions = clf.predict(X_test)print 'decision tree score:',accuracy_score(y_test,predictions)# k-neighborsfrom sklearn import neighborsclf = neighbors. KNeighborsClassifier()clf.fit(X_train,y_train)predictions = clf.predict(X_test)print 'k-neighbors score:',accuracy_score(y_test,predictions)

附图