model.compile(loss='mean_squared_error', optimizer=sgd, class_mode='binary')
history = model.fit(X, y, nb_epoch=10000, batch_size=4, show_accuracy=True)
print() 
score = model.evaluate(X, y)
print() 
print(score)
print(model.predict(np.array([[1, 0]])))
print(model.predict(np.array([[0, 0]])))
print() 
predictions = model.predict(X)
predictions = predictions.T
predictions = [(1 if prediction >= 0.5 else 0) for prediction in predictions[0]
    ]
print(predictions)
print([int(n) for n in y])
Cannot train a neural network in keras