コードは以下
X_train, y_train, X_test, y_test =\
preprocess(scaled_close, SEQ_LEN, train_split = 0.95)
DROPOUT = 0.2
WINDOW_SIZE = SEQ_LEN - 1

model = Sequential()
model.add(LSTM(WINDOW_SIZE, activation = 'tanh', input_shape=(WINDOW_SIZE, X_train.shape[-1]), recurrent_activation= 'hard_sigmoid'))
model.add(Dropout(rate=DROPOUT))
model.add(Dense(units=1))
model.add(Activation('linear'))
BATCH_SIZE = 64
model.compile(
loss='mean_squared_error',
optimizer='adam'
)
history = model.fit(
X_train,
y_train,
epochs=10,
batch_size=BATCH_SIZE,
shuffle=False,
validation_split=0.1
)
print(model.summary())
#Predict
y_hat = model.predict(X_test)
y_test_inverse = scaler.inverse_transform(y_test)
y_hat_inverse = scaler.inverse_transform(y_hat)
result = pd.DataFrame(y_hat_inverse)
result.columns = ['predict']
result['actual'] = y_test_inverse
result.plot()
plt.show()

結果のプロットは以下の通り