SHAPIQ
Tutorial: Exploring SHAP-IQ Visualizations
In this tutorial, we’ll explore a range of SHAP-IQ visualizations that provide insights into how a machine learning model arrives at its predictions. These visuals help break down complex model behavior into interpretable components—revealing both the individual and interactive contributions of features to a specific prediction. Check out the Full Codes here. Installing the dependencies !pip…
How to Use the SHAP-IQ Package to Uncover and Visualize Feature Interactions in Machine Learning Models Using Shapley Interaction Indices (SII)
In this tutorial, we explore how to use the SHAP-IQ package to uncover and visualize feature interactions in machine learning models using Shapley Interaction Indices (SII), building on the foundation of traditional Shapley values. Shapley values are great for explaining individual feature contributions in AI models but fail to capture feature interactions. Shapley interactions go…