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

输出结果

实现代码

#1、

iris = load_iris()

dir(iris)

iris_feature_name = iris.feature_names

iris_features = iris.data

iris_target_name = iris.target_names

iris_target = iris.target

print('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 pydotplus

from IPython.display import Image, display

dot_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, Image

graph = 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 plt

img_path='DT.png'

plt.imshow(img_path)

plt.show()