X_res, y_res, X_test, y_test = generate_train_test_sample(X, y)


X_res = np.expand_dims(X_res, axis=0)
print X_res.shape

seed(2017)
conv = Sequential()
conv.add(Conv1D(2, 2, input_shape=(29, 1), activation='relu'))
conv.add(MaxPooling1D(2))
conv.add(Flatten())
conv.add(Dense(300, activation = 'relu'))

sgd = SGD(lr = 0.1, momentum = 0.9, decay = 0, nesterov = False)
conv.compile(loss = 'binary_crossentropy', optimizer = sgd, metrics =['accuracy'])
conv.fit(X_res, y_res, batch_size = 500, epochs = 15, verbose = 50)