credit.py

import pandas
from sklearn.tree import DecisionTreeClassifier

#Read transaction data
data=pd.read_csv('../input/creditcard.csv')
x_train, x_test, y_train, y_test = train_test_split(data, target, train_size = 0.50)

#train model
model = DecisionTreeClassifier.fit(x_train,y_train)
score = model.score(x_test, y_test)

#print result
print(score)

#test, output fraud/not fraud
model.predict(y_test[3])