fix the input shape to match (:, timesteps, feature) of keras' lstm

Author: Ginurx

StockPricesPredictionProject/pricePredictionLSTM.py

@@ -50,12 +50,12 @@ def create_dataset(dataset, look_back=1):
 testX, testY = create_dataset(test, look_back)
 
 # reshape input to be [samples, time steps, features]
-trainX = np.reshape(trainX, (trainX.shape[0], 1, trainX.shape[1]))
-testX = np.reshape(testX, (testX.shape[0], 1, testX.shape[1]))
+trainX = np.reshape(trainX, (trainX.shape[0], trainX.shape[1], 1))
+testX = np.reshape(testX, (testX.shape[0], testX.shape[1], 1))
 
 # create and fit the LSTM network, optimizer=adam, 25 neurons, dropout 0.1
 model = Sequential()
-model.add(LSTM(25, input_shape=(1, look_back)))
+model.add(LSTM(25, input_shape=(look_back, 1)))
 model.add(Dropout(0.1))
 model.add(Dense(1))
 model.compile(loss='mse', optimizer='adam')