Information Assessment for Individual Modalities in Multimodal Regression Models
Provides methods for quantifying the information gain contributed by individual modalities in multimodal regression models. Information gain is measured using Expected Relative Entropy (ERE) or pseudo-R² metrics, with corresponding p-values and confidence intervals. Currently supports linear and logistic regression models with plans for extension to additional Generalized Linear Models and Cox proportional hazard model.