How can I extract decision tree's node in scikit-learn -
i want extract decision tree's detail information threshold, gini... when searched using google, can find information displaying barely no information node's information. gays know this?
you can export decision tree in dot format, , whatever want it, no 1 forces visualize it: link source code official documentation
from sklearn.datasets import load_iris sklearn import tree iris = load_iris() clf = tree.decisiontreeclassifier() clf = clf.fit(iris.data, iris.target) open("iris.dot", 'w') f: f = tree.export_graphviz(clf, out_file=f)
iris.dot file contains:
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 ; .... }
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