DecisonTreeClassifier.py

import sklearn
import numpy as np
import pandas as pd

buy = pd.read_csv('buys.csv')

from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier

x_fe=['age','income','gender','marital_status']
x=buy[x_fe]
y=buy['buys']

from sklearn import preprocessing
x=x.apply(preprocessing.LabelEncoder().fit_transform)

print(x)


clf = DecisionTreeClassifier(criterion='entropy')
model = clf.fit(x,y)

from IPython.display import Image 
from sklearn import tree
import pydotplus
dot_data = tree.export_graphviz(model, out_file=None,
                                feature_names=x_fe,class_names=['no', 'yes'], filled = True)

graph = pydotplus.graph_from_dot_data(dot_data) 

Image(graph.create_png())
graph.write_png("dtree.png")