Error when checking target: expected dense_1 to have 3 dimensions, but got array with shape (118, 1) : <p>I'm training a model to predict the stock price and input data is close price. I use 45 days data to predict the 46th day's close price and a economic Indicator to be second feature, here is the model:</p>

<pre><code>model = Sequential()
model.add( LSTM( 512, input_shape=(45, 2), return_sequences=True))
model.add( LSTM( 512, return_sequences=True))
model.add( (Dense(1)))
model.compile(loss='mse', optimizer='adam')
history = model.fit( X_train, y_train, batch_size = batchSize, epochs=epochs, shuffle = False)
</code></pre>

<p>When I run this I get the following error:</p>

<blockquote>
  <p>ValueError: Error when checking target: expected dense_1 to have 3
  dimensions, but got array with shape (118, 1)</p>
</blockquote>

<p>However, I <code>print</code> the shape of data and they are:</p>

<pre><code>X_train:(118, 45, 2)
y_train:(118, 1)
</code></pre>

<p>I have no idea why the model is expecting a 3 dimensional output when y_train is (118, 1). Where am I wrong and what should I do?</p>
