# -*- coding: utf-8 -*-
"""
Created on Mon Feb 27 18:01:33 2017
@author: DELL
"""
import DecisionTree as tree
import treePlotter
DataSet, labels = tree.Iris_DataSet()
print('The error number is :')
myTree = tree.createTree(DataSet, labels, 'Entropy', 4, 2)
#4 means number of attributes, 2 means depth of my tree
print('The training result is :')
print(myTree)
treePlotter.createPlot(myTree)
DataSet, labels = tree.Iris_DataSet()
print('The error number is :')
myTree = tree.createTree(DataSet, labels, 'Gini Index', 4, 2)
#4 means number of attributes, 2 means depth of my tree
print('The training result is :')
print(myTree)
treePlotter.createPlot(myTree)
DataSet, labels = tree.Iris_DataSet()
print('The error number is :')
myTree = tree.createTree(DataSet, labels, 'Misclassification error', 4, 2)
#4 means number of attributes, 2 means depth of my tree
print('The training result is :')
print(myTree)
