ML之DT：利用DT(DTC)实现对iris(鸢尾花)数据集进行分类并可视化DT结构
目录
输出结果
实现代码
输出结果
实现代码
#1、iris = load_iris()dir(iris)iris_feature_name = iris.feature_namesiris_features = iris.datairis_target_name = iris.target_namesiris_target = iris.targetprint('iris_feature_name','\n',iris_feature_name)print('iris_features前5','\n',iris_features[:5,:],iris_features.shape)print('iris_target_name','\n',iris_target_name)print('iris_target','\n',iris_target)#2、clf = tree.DecisionTreeClassifier(max_depth=4)clf = clf.fit(iris_features, iris_target)#3、import pydotplusfrom IPython.display import Image, displaydot_data = tree.export_graphviz(clf,out_file = None,feature_names = iris_feature_name,class_names = iris_target_name,filled=True,rounded=True)from IPython.display import display, Imagegraph = pydotplus.graph_from_dot_data(dot_data)# graph.write_png(r"DT.png")display(Image(graph.create_png()))Image(graph.create_png())import matplotlib.pyplot as pltimg_path='DT.png'plt.imshow(img_path)plt.show()
