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@mmschlk mmschlk released this 29 Nov 16:27
· 704 commits to main since this release
v.0.0.4-alpha
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New Approximators

This release adds new approximation methods to shapiq and makes all interaction calculations faster and more memory efficient.

ShapIQ approximator

This release adds the shapiq.approximator.ShapIQ approximator as proposed in this paper (NeurIPS'23).
ShapIQ can approximate any cardinal interaction index (CII) like the Shapley Interaction Index (SII), the Shapley Taylor Index (STI), or the Faithful Shapley Interaction index (FSI).

Regression Estimator for FSI

The shapiq.approximator.RegressionFSI regression estimator, which is only available for FSI, was proposed in this paper (JMLR'23). It is similar to KernelSHAP in that it leverages a weighted least squares representation for the interaction index and solves this by estimating this regression problem.

Permutation Sampling for STI

The permutation sampling currently implemented for the SII (shapiq.approximator.PermutationSamplingSII) can also be extended to the STI. The new shapiq.approximator.PermutationSamplingSTI uses the traditional permutation sampling approach to compute STI scores.

List of PRs

Full Changelog: v0.0.3-alpha...v.0.0.4-alpha

Contributors

mmschlk
Assets 4
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