Updated decision tree tutorial, need to evaulate if good idea

Author: mGalarnyk

Sklearn/DecisionTrees/.ipynb_checkpoints/DecisionTreeAnatomy-checkpoint.ipynb

@@ -1,12 +1,12 @@
 digraph Tree {
 node [shape=box] ;
-0 [label="petal length (cm) <= 2.35\ngini = 0.665\nsamples = 112\nvalue = [37, 34, 41]\nclass = virginica"] ;
-1 [label="gini = 0.0\nsamples = 37\nvalue = [37, 0, 0]\nclass = setosa"] ;
+0 [label="petal length (cm) <= 2.45\ngini = 0.665\nsamples = 112\nvalue = [38, 40, 34]\nclass = versicolor"] ;
+1 [label="gini = 0.0\nsamples = 38\nvalue = [38, 0, 0]\nclass = setosa"] ;
 0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
-2 [label="petal length (cm) <= 4.95\ngini = 0.496\nsamples = 75\nvalue = [0, 34, 41]\nclass = virginica"] ;
+2 [label="petal length (cm) <= 4.95\ngini = 0.497\nsamples = 74\nvalue = [0, 40, 34]\nclass = versicolor"] ;
 0 -> 2 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
-3 [label="gini = 0.153\nsamples = 36\nvalue = [0, 33, 3]\nclass = versicolor"] ;
+3 [label="gini = 0.136\nsamples = 41\nvalue = [0, 38, 3]\nclass = versicolor"] ;
 2 -> 3 ;
-4 [label="gini = 0.05\nsamples = 39\nvalue = [0, 1, 38]\nclass = virginica"] ;
+4 [label="gini = 0.114\nsamples = 33\nvalue = [0, 2, 31]\nclass = virginica"] ;
 2 -> 4 ;
 }