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:
explainer_1.0.2.tar.gz
explainer_1.0.2.zip(r-4.7-any)explainer_1.0.2.zip(r-4.6-any)explainer_1.0.2.zip(r-4.5-any)
explainer_1.0.2.tgz(r-4.6-any)explainer_1.0.2.tgz(r-4.5-any)
explainer_1.0.2.tar.gz(r-4.7-any)explainer_1.0.2.tar.gz(r-4.6-any)
explainer_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
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/docs site:https://persimune.github.io
aiai-pipelineai-toolsclassificationclinical-researchexplainabilityexplainable-aiinterpretabilitymachine-learningmachine-learning-pipelinesml-toolsregressionshapstatistics
Last updated from:627d068d40. Checks:7 WARNING, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | WARNING | 153 | ||
| source / vignettes | OK | 240 | ||
| linux-release | WARNING | 174 | ||
| macos-release | WARNING | 147 | ||
| macos-oldrel | WARNING | 157 | ||
| windows-devel | WARNING | 121 | ||
| windows-release | WARNING | 103 | ||
| windows-oldrel | WARNING | 108 | ||
| wasm-release | OK | 127 |
Exports:eCM_ploteDecisionCurveeFairnessePerformanceeROC_ploteSHAP_ploteSHAP_plot_multiclasseSHAP_plot_regrange01regressmdl_evalSHAPclustShapFeaturePlotShapPartialPlot
Dependencies:abindaskpassbackportsbase64encbayestestRbitopsbootbroombslibcachemcarcarDatacaToolscheckmateclasscliclockcodetoolscolorspaceconfintrcorrplotcowplotcpp11crosstalkcurlcvmsdata.tabledatawizardDerivdiagramdigestdoBydplyreggevaluatefarverfastmapfontawesomeforecastFormulafracdifffsfuturefuture.applygenericsggplot2ggpmiscggppggpubrggrepelggsciggsignifglobalsgluegowergridExtragroupdata2gtablehardhathighrhtmltoolshtmlwidgetshttrinsightipredisobandjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelavalazyevallifecyclelistenvlme4lmtestlubridatemagrittrMASSMatrixMatrixModelsmemoisemgcvmimeminqamodelrMuMInnlmenloptrnnetnumbersnumDerivopensslotelparallellyparameterspbkrtestpillarpkgconfigplotlyplyrpolynompROCprodlimprogressrpromisespurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackrearrrrecipesreformulasrlangrmarkdownrpartrstatixS7sassscalesshapeSparseMsparsevctrssplus2RSQUAREMstringistringrsurvivalsystibbletidyrtidyselecttimechangetimeDatetinytextzdburcautf8vctrsviridisLitewithrwritexlxfunxtsyamlzoo
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 |
