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ale 0.3.0

The most significant updates are the addition of p-values for the ALE statistics, the launching of a pkgdown website which will henceforth host the development version of the package, and parallelization of core functions with a resulting performance boost.

Breaking changes

Other user-visible changes

Under the hood

Known issues to be addressed in a future version

ale 0.2.0

This version introduces various ALE-based statistics that let ALE be used for statistical inference, not just interpretable machine learning. A dedicated vignette introduces this functionality (see “ALE-based statistics for statistical inference and effect sizes” from the vignettes link on the main CRAN page at https://CRAN.R-project.org/package=ale). We introduce these statistics in detail in a working paper: Okoli, Chitu. 2023. “Statistical Inference Using Machine Learning and Classical Techniques Based on Accumulated Local Effects (ALE).” arXiv. https://doi.org/10.48550/arXiv.2310.09877. Please note that they might be further refined after peer review.

Breaking changes

Other user-visible changes

Under the hood

By far the most extensive changes have been to assure the accuracy and stability of the package from a software engineering perspective. Even though these are not visible to users, they make the package more robust with hopefully fewer bugs. Indeed, the extensive data validation may help users debug their own errors.

Known issues to be addressed in a future version

ale 0.1.0

This is the first CRAN release of the ale package. Here is its official description with the initial release:

Accumulated Local Effects (ALE) were initially developed as a model-agnostic approach for global explanations of the results of black-box machine learning algorithms. (Apley, Daniel W., and Jingyu Zhu. “Visualizing the effects of predictor variables in black box supervised learning models.” Journal of the Royal Statistical Society Series B: Statistical Methodology 82.4 (2020): 1059-1086 doi:10.1111/rssb.12377.) ALE has two primary advantages over other approaches like partial dependency plots (PDP) and SHapley Additive exPlanations (SHAP): its values are not affected by the presence of interactions among variables in a model and its computation is relatively rapid. This package rewrites the original code from the ‘ALEPlot’ package for calculating ALE data and it completely reimplements the plotting of ALE values.

(This package uses the same GPL-2 license as the {ALEPlot} package.)

This initial release replicates the full functionality of the {ALEPlot} package and a lot more. It currently presents three functions:

This release provides more details in the following vignettes (they are all available from the vignettes link on the main CRAN page at https://CRAN.R-project.org/package=ale):

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.