decision tree

digraph Tree {
node [shape=box] ;
0 [label="H <= 0.5\nentropy = 0.996\nsamples = 13\nvalue = [6, 7]\nclass = 1"] ;
1 [label="Idade <= 28.5\nentropy = 0.971\nsamples = 10\nvalue = [6, 4]\nclass = 0"] ;
0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
2 [label="B <= 0.5\nentropy = 0.918\nsamples = 6\nvalue = [2, 4]\nclass = 1"] ;
1 -> 2 ;
3 [label="Idade <= 26.0\nentropy = 0.918\nsamples = 3\nvalue = [2, 1]\nclass = 0"] ;
2 -> 3 ;
4 [label="entropy = 0.0\nsamples = 2\nvalue = [2, 0]\nclass = 0"] ;
3 -> 4 ;
5 [label="entropy = 0.0\nsamples = 1\nvalue = [0, 1]\nclass = 1"] ;
3 -> 5 ;
6 [label="entropy = 0.0\nsamples = 3\nvalue = [0, 3]\nclass = 1"] ;
2 -> 6 ;
7 [label="entropy = 0.0\nsamples = 4\nvalue = [4, 0]\nclass = 0"] ;
1 -> 7 ;
8 [label="entropy = 0.0\nsamples = 3\nvalue = [0, 3]\nclass = 1"] ;
0 -> 8 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
}

gistfile1.txt

# check this link: <http://webgraphviz.com/>. it will create a shitty visualization