visible = Input(shape=(X.shape[1],))
hidden1 = Dense(512, activation='relu')(visible)
hidden2 = Dense(256, activation='relu')(hidden1)
hidden3 = Dense(128, activation='relu')(hidden2)
output = Dense(1, activation='sigmoid')(hidden3)
model = Model(inputs=visible, outputs=output)
model.compile(optimizer = 'adam', loss = 'mean_squared_error',
metrics = ['accuracy'])
model.fit(X_train, y_train, batch_size = 10, epochs = 100)