Release v1.1.0 (2024-11-07) · mmschlk/shapiq

New Features and Improvements

adds computation of the Egalitarian Core (EC) and Egalitarian Least-Core (ELC) to the ExactComputer #182
adds waterfall_plot #34 that visualizes the contributions of features to the model prediction
adds BaselineImputer #107 which is now responsible for handling the sample_replacements parameter. Added a DeprecationWarning for the parameter in MarginalImputer, which will be removed in the next release.
adds joint_marginal_distribution parameter to MarginalImputer with default value True #261
renames explanation graph to si_graph
get_n_order now has optional lower/upper limits for the order
computing metrics for benchmarking now tries to resolve not-matching interaction indices and will throw a warning instead of a ValueError #179
add a legend to benchmark plots #170
refactored the shapiq.games.benchmark module into a separate shapiq.benchmark module by moving all but the benchmark games into the new module. This closes #169 and makes benchmarking more flexible and convenient.
a shapiq.Game can now be called more intuitively with coalitions data types (tuples of int or str) and also allows to add player_names to the game at initialization #183
improve tests across the package

adds a notebook showing how to use custom tree models with the TreeExplainer #66
adds a notebook show how to use the shapiq.Game API to create custom games #184
adds a notebook showing hot to visualize interactions #252
adds a notebook showing how to compute Shapley values with shapiq #193
adds a notebook for conducting data valuation #190
adds a notebook showcasing introducing the Core and how to compute it with shapiq #191

fixes a bug with SIs not adding up to the model prediction because of wrong values in the empty set #264
fixes a bug that TreeExplainer did not have the correct baseline_value when using XGBoost models #250
fixes the force plot not showing and its baseline value

Full Changelog: v1.0.1...v1.1.0