Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2023

P. MishraExplainable AI Recipes https://doi.org/10.1007/978-1-4842-9029-3_5

5. Explainability for Natural Language Processing

Pradeepta Mishra¹  

(1)

Bangalore, Karnataka, India

 

Natural language processing tasks such as text classification and sentiment analysis can be explained using explainable AI libraries such as SHAP and ELI5. The objective of explaining the text classification tasks or sentiment analysis tasks is to let the user know how a decision was made. The predictions are generated using a supervised learning model for unstructured text data. The input is a text sentence or many sentences or phrases, and we train a machine learning model to perform ...