How to model RNN with Attention Mechanism for Non-Text Classification

Question

With the help of code can you tell me How to model RNN with Attention Mechanism for Non-Text Classification?

Answer 1

To model a RNN with an Attention Mechanism for non-text classification, use a RNN (e.g., LSTM) to extract features and an attention layer to focus on important time steps before classification.

Here is the code snippet you can refer to:

In the above code, we are using the following key points:

• Uses LSTM for feature extraction from sequential data.
• Implements Attention Mechanism to focus on relevant parts of the sequence.
• Uses Dense layers for final classification.
• Model is compiled with Adam optimizer and binary cross-entropy loss for classification.

Hence, the combination of RNN (LSTM) and Attention Mechanism enhances feature extraction and improves classification accuracy for non-text sequential data.