Stable Local Interpretable Model-Agnostic Explanations (LIME, OptiLIME, BayLIME, ALIME)


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Documentation for package ‘limestab’ version 0.1.0

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limestab-package limestab: Stable LIME, OptiLIME, BayLIME and ALIME
alime_explainer Create an ALIME explainer
alime_explain_instance Explain a single instance with ALIME
bayesian_optimisation Bayesian optimisation of a scalar objective
bayesian_ridge_fit Bayesian ridge regression (Tipping 2001 / MacKay 1992)
baylime_explainer Create a BayLIME explainer
baylime_explain_instance Explain a single instance with BayLIME
calculate_distances Euclidean distance of every row to an instance
compute_cov_metrics Coefficient-of-variation metrics across repeated runs
compute_csi Coefficient Stability Index (CSI)
compute_icsi Interval-Based Coefficient Stability Index (ICSI)
compute_mad_stdevs Robust standard deviation from repeated coefficients
compute_mrms Median Rank Matching Stability of features across repeated runs
compute_pcsi PCSI stability indices
compute_vsi Variable Stability Index (VSI)
compute_wls_stdevs Standard deviations of weighted ridge coefficients
default_kernel_width Default LIME kernel width for tabular data
fit_gp Fit a 1-D Gaussian process (Matern 3/2 kernel)
fit_weighted_ridge Weighted ridge regression with an unpenalised intercept
generate_perturbations Generate a perturbed neighbourhood in standardised feature space
limestab limestab: Stable LIME, OptiLIME, BayLIME and ALIME
lime_check_stability Repeat an explanation and compute every stability metric
lime_confidence_intervals Confidence intervals for a LIME-style explanation
lime_explainer Create a LIME explainer
lime_explain_instance Explain a single instance with LIME
lime_kernel LIME exponential kernel
optilime OptiLIME: choose the LIME kernel width by Bayesian optimisation
optilime_score OptiLIME objective (reflected local R-squared)
predict.optilime_gp Predict method for optilime_gp objects
select_features Select the features used by a LIME-style local model
weighted_r2 Weighted R-squared