import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from sklearn import tree
banknot_df=pd.read_csv('data_banknote_authentication.txt', sep = ',', header = None,
names = ["varyans","carpiklik", "basiklik", "entropi", "sinif" ])
banknot_df.head()
banknot_df.info()
X = banknot_df.drop('sinif', axis = 1)
y = banknot_df['sinif']
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.20, random_state = 60)
from sklearn.tree import DecisionTreeClassifier
classifier = DecisionTreeClassifier()
classifier.fit(X_train, y_train)
y_pred = classifier.predict(X_test)
print (y_pred)