from sklearn import linear_model

# x = [[20, 3],
#      [23, 7],
#      [31, 10],
#      [42, 13],
#      [50, 7],
#      [60, 5]]
# y = [0, 1, 1, 1, 0, 0]
# lr = linear_model.LogisticRegression()
# lr.fit(x, y)
# testX = [[28, 8]]
# label = lr.predict(testX)
# print("predicted label = ", label)
#
# prob = lr.predict_proba(testX)
# print("probability = ", prob)

import tensorflow as tf
tf.compat.v1.disable_eager_execution()
hello = tf.constant("hello, world!")
sess = tf.compat.v1.Session()
result = sess.run(hello)
sess.close()
print(result)