python决策树预测模型,python决策树算法毕业设计

python决策树分类代码#决策树分类importpandasaspdfromsklearn.treeimportdecisiontreeclassifier # DecisionTreeClassifier函数froms klearn.model _ selectionimporttrain _ test _ splitfromsklearnimportmetrics #分类结果评估函数data=PD ' ' yx1x2x 3010.697.460011.7740.3760210.634.2640310.608.318041.556.215051.403.237161.481.149171 92120.639.1610130.6570.1980140.360.3701150.5930.0422160.719 0.1031' ' x=data [ ' x1 '，' x2 '，' x3 y_train train_size=0.8 ) print (训练集和测试集shape )，x_train.shape，y_train.shape，x_test.shape y _ test.shape (model=decisiontreeclassifier (criterion=' entropy ' )实例化模型decisiontreeclassifier ) (model.fit ) 在训练集中模型print(model )输出模型)测试集中模型expected=y_test # )测试样本预期输出predicted=model.predict ) x_test )测试样本预测输出结果print (metrics.class ification _ report ) expected， predicted ) )输出结果、精度、召回率、f-1分数打印) metrics.confusion _ mming predicted (#混淆矩阵AUC=metrics.roc _ AUC _