block15.python

from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score
# split into train and test sets
X_train, X_test, y_train, y_test = train_test_split(X_clf, y_clf, test_size=0.33, random_state=1)
# fit the model
model = LogisticRegression(solver='liblinear')
model.fit(X_train, y_train)
# evaluate the model
yhat = model.predict(X_test)
# evaluate predictions
accuracy = accuracy_score(y_test, yhat)
print('Accuracy: %.2f' % (accuracy*100))