Package: explainer 1.0.2

Ramtin Zargari Marandi

explainer: Machine Learning Model Explainer

It enables detailed interpretation of complex classification and regression models through Shapley analysis including data-driven characterization of subgroups of individuals. Furthermore, it facilitates multi-measure model evaluation, model fairness, and decision curve analysis. Additionally, it offers enhanced visualizations with interactive elements.

Authors:Ramtin Zargari Marandi [aut, cre]

explainer_1.0.2.tar.gz
explainer_1.0.2.zip(r-4.5)explainer_1.0.2.zip(r-4.4)explainer_1.0.2.zip(r-4.3)
explainer_1.0.2.tgz(r-4.5-any)explainer_1.0.2.tgz(r-4.4-any)explainer_1.0.2.tgz(r-4.3-any)
explainer_1.0.2.tar.gz(r-4.5-noble)explainer_1.0.2.tar.gz(r-4.4-noble)
explainer_1.0.2.tgz(r-4.4-emscripten)explainer_1.0.2.tgz(r-4.3-emscripten)
explainer.pdf |explainer.html✨
explainer/json (API)

# Install 'explainer' in R:

install.packages('explainer', repos = c('https://persimune.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/persimune/explainer/issues

Pkgdown site:https://persimune.github.io

On CRAN:

ai classification clinical-research explainability explainable-ai interpretability machine-learning regression shap statistics

5.43 score 15 stars 12 scripts 301 downloads 13 exports 155 dependencies

Last updated 6 months agofrom:260bd43acb. Checks:1 OK, 1 ERROR, 7 NOTE. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Mar 23 2025
R-4.5-win	NOTE	Mar 23 2025
R-4.5-mac	NOTE	Mar 23 2025
R-4.5-linux	ERROR	Mar 23 2025
R-4.4-win	NOTE	Mar 23 2025
R-4.4-mac	NOTE	Mar 23 2025
R-4.4-linux	NOTE	Mar 23 2025
R-4.3-win	NOTE	Mar 23 2025
R-4.3-mac	NOTE	Mar 23 2025

Exports:eCM_plot eDecisionCurve eFairness ePerformance eROC_plot eSHAP_plot eSHAP_plot_multiclass eSHAP_plot_reg range01 regressmdl_eval SHAPclust ShapFeaturePlot ShapPartialPlot

Dependencies:abind askpass backports base64enc bayestestR boot broom bslib cachem car carData checkmate class cli clock codetools colorspace confintr corrplot cowplot cpp11 crosstalk curl cvms data.table datawizard Deriv diagram digest doBy dplyr egg evaluate fansi farver fastmap fontawesome Formula fs future future.apply generics ggplot2 ggpmisc ggpp ggpubr ggrepel ggsci ggsignif globals glue gower gridExtra groupdata2 gtable hardhat highr htmltools htmlwidgets httr insight ipred isoband jquerylib jsonlite KernSmooth knitr labeling later lattice lava lazyeval lifecycle listenv lme4 lmodel2 lubridate magrittr MASS Matrix MatrixModels memoise mgcv microbenchmark mime minqa modelr multcomp multcompView MuMIn munsell mvtnorm nlme nloptr nnet numbers numDeriv openssl parallelly parameters pbkrtest pillar pkgconfig plotly plyr polynom pROC prodlim progressr promises purrr quantreg R6 rappdirs rbibutils RColorBrewer Rcpp RcppEigen Rdpack rearrr recipes reformulas rlang rmarkdown rpart rstatix sandwich sass scales shape SparseM sparsevctrs splus2R SQUAREM stringi stringr survival sys TH.data tibble tidyr tidyselect timechange timeDate tinytex tzdb utf8 vctrs viridisLite withr writexl xfun xts yaml zoo

explainer-vignette

Rendered fromexplainer-vignette.Rmdusingknitr::rmarkdownon Mar 23 2025.

Last update: 2024-09-23
Started: 2024-09-23

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Enhanced Confusion Matrix Plot	eCM_plot
Decision Curve Plot	eDecisionCurve
Enhanced Fairness Analysis	eFairness
Enhanced Performance Evaluation	ePerformance
Enhanced ROC and Precision-Recall Plots	eROC_plot
Enhanced SHAP Analysis for Regression Models	eSHAP_plot_reg
SHAP clustering	SHAPclust
SHAP Values versus Feature Values	ShapFeaturePlot
SHAP Partial Plot	ShapPartialPlot