When developing a recurrent neural network model, we come across situations where we need to make several decisions related to the network. These decisions could include trying a different activation function rather than the default one that we had used. Let's make such changes and see what impact they have on the movie review sentiment classification performance of the model.
In this section, we will experiment with the following four factors:
- Number of units in the simple RNN layer
- Using different activation functions in the simple RNN layer
- Adding more recurrent layers
- Changes in the maximum length for padding sequences
