run chapter 05, 06

images/decision_trees/iris_tree.dot

@@ -0,0 +1,13 @@
+digraph Tree {
+node [shape=box, style="filled, rounded", color="black", fontname=helvetica] ;
+edge [fontname=helvetica] ;
+0 [label="꽃잎 길이 (cm) <= 2.45\ngini = 0.667\nsamples = 150\nvalue = [50, 50, 50]\nclass = setosa", fillcolor="#e5813900"] ;
+1 [label="gini = 0.0\nsamples = 50\nvalue = [50, 0, 0]\nclass = setosa", fillcolor="#e58139ff"] ;
+0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
+2 [label="꽃잎 폭 (cm) <= 1.75\ngini = 0.5\nsamples = 100\nvalue = [0, 50, 50]\nclass = versicolor", fillcolor="#39e58100"] ;
+0 -> 2 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
+3 [label="gini = 0.168\nsamples = 54\nvalue = [0, 49, 5]\nclass = versicolor", fillcolor="#39e581e5"] ;
+2 -> 3 ;
+4 [label="gini = 0.043\nsamples = 46\nvalue = [0, 1, 45]\nclass = virginica", fillcolor="#8139e5f9"] ;
+2 -> 4 ;
+}

images/decision_trees/regression_tree.dot

@@ -0,0 +1,17 @@
+digraph Tree {
+node [shape=box, style="filled, rounded", color="black", fontname=helvetica] ;
+edge [fontname=helvetica] ;
+0 [label="x1 <= 0.197\nmse = 0.098\nsamples = 200\nvalue = 0.354", fillcolor="#e5813953"] ;
+1 [label="x1 <= 0.092\nmse = 0.038\nsamples = 44\nvalue = 0.689", fillcolor="#e58139c7"] ;
+0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
+2 [label="mse = 0.018\nsamples = 20\nvalue = 0.854", fillcolor="#e58139ff"] ;
+1 -> 2 ;
+3 [label="mse = 0.013\nsamples = 24\nvalue = 0.552", fillcolor="#e5813998"] ;
+1 -> 3 ;
+4 [label="x1 <= 0.772\nmse = 0.074\nsamples = 156\nvalue = 0.259", fillcolor="#e5813933"] ;
+0 -> 4 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
+5 [label="mse = 0.015\nsamples = 110\nvalue = 0.111", fillcolor="#e5813900"] ;
+4 -> 5 ;
+6 [label="mse = 0.036\nsamples = 46\nvalue = 0.615", fillcolor="#e58139ad"] ;
+4 -> 6 ;
+}