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from sklearn.tree import DecisionTreeRegressor

import pandas as pd

import pandas as pd
fraud_data_path = '../input/credit_fraud_sytn.csv'
fraud_data = pd.read_csv(fraud_data_path)

fraud_data.columns

y = fraud_data.isFradulent
feature_names = ['Average Amount/transaction/day', 'Transaction_amount', 'isForeignTransaction', 'isHighRiskCountry']
X = fraud_data[feature_names]

from sklearn.tree import DecisionTreeRegressor
fraud_model = DecisionTreeRegressor(random_state=1)
fraud_model.fit(X, y)