Decision Tree.py

#!/usr/bin/env python
# coding: utf-8

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from sklearn.datasets import load_iris
import pandas as pd


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import pandas as pd
data=pd.read_csv(r'C:\Users\18521\Downloads\iris.csv')
data.head()


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data.shape
X=data.iloc[:,0:4]
Y=data.iloc[:,-1]
print(Y)


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from sklearn.model_selection import train_test_split
X_train, X_test, Y_train, Y_test =train_test_split(X, Y, train_size= 0.8, random_state=0)


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X_test.shape


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from sklearn.tree import DecisionTreeClassifier
classifier = DecisionTreeClassifier(criterion= "entropy",random_state=0)
classifier.fit(X_train, Y_train)


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import matplotlib.pyplot as plt
from sklearn.tree import plot_tree
#Use the pandas apply method to numerically encode our attrition target variable


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plt.figure(figsize=(10,11))
plot_tree(classifier)
plt.show


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classifier.score(X_train,Y_train)


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classifier.score(X_test,Y_test)


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