Scikit learn 如何提取决策树'；scikit学习中的s节点

我想提取决策树的详细信息，如阈值、基尼…

您可以以格式导出决策树，并对其执行任何操作，没有人强迫您将其可视化：

iris.dot文件现在包含：

digraph Tree {
node [shape=box] ;
0 [label="X[3] <= 0.8\ngini = 0.6667\nsamples = 150\nvalue = [50, 50, 50]"] ;
1 [label="gini = 0.0\nsamples = 50\nvalue = [50, 0, 0]"] ;
0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
2 [label="X[3] <= 1.75\ngini = 0.5\nsamples = 100\nvalue = [0, 50, 50]"] ;
0 -> 2 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
3 [label="X[2] <= 4.95\ngini = 0.168\nsamples = 54\nvalue = [0, 49, 5]"] ;
2 -> 3 ;
....
}

有向图树{
节点[shape=box]；
0[label=“X[3]
digraph Tree {
node [shape=box] ;
0 [label="X[3] <= 0.8\ngini = 0.6667\nsamples = 150\nvalue = [50, 50, 50]"] ;
1 [label="gini = 0.0\nsamples = 50\nvalue = [50, 0, 0]"] ;
0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
2 [label="X[3] <= 1.75\ngini = 0.5\nsamples = 100\nvalue = [0, 50, 50]"] ;
0 -> 2 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
3 [label="X[2] <= 4.95\ngini = 0.168\nsamples = 54\nvalue = [0, 49, 5]"] ;
2 -> 3 ;
....
}