Package index • xplainfi

Importance Measures

Base class

FeatureImportanceMethod: Feature Importance Method Class

c(<FeatureImportanceMethod>): Combine two FeatureImportanceMethod objects

Perturbation-Based Importance Measures

Methods which perturb features of interest either marginally (PFI) or conditionally on all (CFI) or a subset of remaining features (RFI)

PerturbationImportance: Perturbation Feature Importance Base Class

PFI: Permutation Feature Importance

CFI: Conditional Feature Importance

RFI: Relative Feature Importance

Model Refitting Measures

Methods which refit models with one (or more) features omitted (LOCO) or included (LOCI).

LOCO: Leave-One-Covariate-Out (LOCO)

LOCI: Leave-One-Covariate-In (LOCI)

Shapley-Based Approaches

Shapley Additive Global Importance (SAGE) in marginal and conditional variants

SAGE: Shapley Additive Global Importance (SAGE) Base Class

MarginalSAGE: Marginal SAGE

ConditionalSAGE: Conditional SAGE

Sampling Infrastructure

Marginal and conditional sampling

FeatureSampler: Feature Sampler Class

MarginalSampler: Marginal Feature Sampler

ConditionalSampler: Conditional Feature Sampler

ARFSampler: ARF-based Conditional Sampler

KnockoffSampler: Knockoff-based Conditional Sampler

Utilities

`%||%`: Default value for NULL

Data simulation

sim_dgp_ewald(): Simulate data as in Ewald et al. (2024)

sim_dgp_correlated() sim_dgp_mediated() sim_dgp_confounded() sim_dgp_interactions() sim_dgp_independent(): Simulation DGPs for Feature Importance Method Comparison