title: How to choose LSTM Keras parameters?
body: <p>I have multiple time series in input and I want to properly build an LSTM model.  </p>
  
  <p>I'm really confused about how to choose the parameters. My code:</p>
  
  <pre><code>model.add(keras.layers.LSTM(hidden_nodes, input_shape=(window, num_features), consume_less="mem"))
  model.add(Dropout(0.2))
  model.add(keras.layers.Dense(num_features, activation='sigmoid'))
  
  optimizer = keras.optimizers.SGD(lr=learning_rate, decay=1e-6, momentum=0.9, nesterov=True)
  </code></pre>
  
  <p>I want to understand, for each line, the meaning of the input parameters and how those have to be choosed.  </p>
  
  <p>Actually I don't have any problems with the code but I need to understand clearly the parameters in order to obtain better results.  </p>
  
  <p>Thanks a lot!</p>