DT with example

from sklearn import tree                                                     
clf = tree.DecisionTreeClassifier()                                           

#[height, hair-length, voice-pitch]                                           
X = [ [180, 15,0],                                                           
      [167, 42,1],                                                           
      [136, 35,1],                                                           
      [174, 15,0],                                                           
      [141, 28,1]]                                                           

Y = ['man', 'woman', 'woman', 'man', 'woman']                                 

clf = clf.fit(X, Y)                                                           
prediction = clf.predict([[133, 37,1]])                                       
print(prediction)

______________________________________________________

import pydotplus

from sklearn.datasets import load_iris

from sklearn import tree

import collections

# Data Collection

X = [ [180, 15,0],    

      [177, 42,0],

      [136, 35,1],

      [174, 65,0],

      [141, 28,1]]

Y = ['man', 'woman', 'woman', 'man', 'woman']    

data_feature_names = [ 'height', 'hair length', 'voice pitch' ]

# Training

clf = tree.DecisionTreeClassifier()

clf = clf.fit(X,Y)

# Visualize data

dot_data = tree.export_graphviz(clf,

                                feature_names=data_feature_names,

                                out_file=None,

                                filled=True,

                                rounded=True)

graph = pydotplus.graph_from_dot_data(dot_data)

colors = ('turquoise', 'orange')

edges = collections.defaultdict(list)

for edge in graph.get_edge_list():

    edges[edge.get_source()].append(int(edge.get_destination()))

for edge in edges:

    edges[edge].sort()    

    for i in range(2):

        dest = graph.get_node(str(edges[edge][i]))[0]

        dest.set_fillcolor(colors[i])

graph.write_png('tree.png')