SHAP values for Explaining CNN-based Text Classification Models

Understand

Deep neural networks are increasingly used in natural language processing (NLP) models.

• However, the need to interpret and explain the results from complex algorithms are limiting their widespread adoption in regulated industries such as banking.
• There has been recent work on interpretability of machine learning algorithms with structured data.
• But there are only limited techniques for NLP applications where the problem is more challenging due to the size of the vocabulary, high-dimensional nature, and the need to consider textual coherence and language structure.