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决策树可视化

决策树可视化

作者: 凌霄文强 | 来源:发表于2019-06-15 20:53 被阅读0次
    import numpy as np
    import pandas as  pd
    import pydotplus
    
    
    from sklearn.datasets import load_iris
    iris = load_iris()
    
    from sklearn.cross_validation import train_test_split
    # 把数据分为测试数据和验证数据
    train_data, test_data, train_target, test_target = train_test_split(iris.data, iris.target, test_size=0.2,
                                                                        random_state=1)
    # Model(建模)-引入决策树
    from sklearn import tree
    
    # 建立一个分类器
    clf = tree.DecisionTreeClassifier(criterion="entropy")
    # 训练集进行训练
    clf.fit(train_data, train_target)
    
    # 画图方法1-生成dot文件
    with open('treeone.dot', 'w') as f:
        dot_data = tree.export_graphviz(clf, out_file=None)
        f.write(dot_data)
    
    # 画图方法2-生成pdf文件
    dot_data = tree.export_graphviz(clf, out_file=None, feature_names=clf.feature_importances_,
                                    filled=True, rounded=True, special_characters=True)
    graph = pydotplus.graph_from_dot_data(dot_data)
    ###保存图像到pdf文件
    graph.write_pdf("treetwo.pdf")
    
    image.png

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