DecisionTreeSample-Assigment1-3/tree_representation.dot at master · cbalkig/DecisionTreeSample-Assigment1-3 · GitHub

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digraph Tree {
node [shape=box] ;
0 [label="B <= 0.5\nentropy = 1.0\nsamples = 8\nvalue = [4, 4]"] ;
1 [label="A <= 0.5\nentropy = 0.811\nsamples = 4\nvalue = [3, 1]"] ;
0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
2 [label="entropy = 0.0\nsamples = 2\nvalue = [2, 0]"] ;
1 -> 2 ;
3 [label="C <= 0.5\nentropy = 1.0\nsamples = 2\nvalue = [1, 1]"] ;
1 -> 3 ;
4 [label="entropy = 0.0\nsamples = 1\nvalue = [1, 0]"] ;
3 -> 4 ;
5 [label="entropy = 0.0\nsamples = 1\nvalue = [0, 1]"] ;
3 -> 5 ;
6 [label="C <= 0.5\nentropy = 0.811\nsamples = 4\nvalue = [1, 3]"] ;
0 -> 6 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
7 [label="entropy = 0.0\nsamples = 2\nvalue = [0, 2]"] ;
6 -> 7 ;
8 [label="A <= 0.5\nentropy = 1.0\nsamples = 2\nvalue = [1, 1]"] ;
6 -> 8 ;
9 [label="entropy = 0.0\nsamples = 1\nvalue = [0, 1]"] ;
8 -> 9 ;
10 [label="entropy = 0.0\nsamples = 1\nvalue = [1, 0]"] ;
8 -> 10 ;
}