Package: survex 1.2.0.9001

Mikołaj Spytek

survex: Explainable Machine Learning in Survival Analysis

Survival analysis models are commonly used in medicine and other areas. Many of them are too complex to be interpreted by human. Exploration and explanation is needed, but standard methods do not give a broad enough picture. 'survex' provides easy-to-apply methods for explaining survival models, both complex black-boxes and simpler statistical models. They include methods specific to survival analysis such as SurvSHAP(t) introduced in Krzyzinski et al., (2023) <doi:10.1016/j.knosys.2022.110234>, SurvLIME described in Kovalev et al., (2020) <doi:10.1016/j.knosys.2020.106164> as well as extensions of existing ones described in Biecek et al., (2021) <doi:10.1201/9780429027192>.

Authors:Mikołaj Spytek [aut, cre], Mateusz Krzyziński [aut], Sophie Langbein [aut], Hubert Baniecki [aut], Lorenz A. Kapsner [ctb], Przemyslaw Biecek [aut]

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Bug tracker:https://github.com/modeloriented/survex/issues

On CRAN:

biostatisticsbrier-scorescensored-datacox-modelcox-regressionexplainable-aiexplainable-machine-learningexplainable-mlexplanatory-model-analysisinterpretable-machine-learninginterpretable-mlmachine-learningprobabilistic-machine-learningshapsurvival-analysistime-to-eventvariable-importancexai

31 exports 95 stars 4.30 score 109 dependencies 91 scripts 362 downloads

Last updated 3 months agofrom:cb0852a385. Checks:OK: 5 ERROR: 2. Indexed: yes.

Exports:brier_scorec_indexcd_auccumulative_hazard_to_survivalexplainexplain_survivalextract_predict_survshapintegrated_brier_scoreintegrated_cd_aucloss_adapt_mlr3probaloss_brier_scoreloss_integrateloss_integrated_brier_scoreloss_one_minus_c_indexloss_one_minus_cd_aucloss_one_minus_integrated_cd_aucmodel_diagnosticsmodel_partsmodel_performancemodel_profilemodel_profile_2dmodel_survshappredict_partspredict_profilerisk_from_chfset_theme_survexsurv_model_infosurvival_to_cumulative_hazardtheme_default_survextheme_vertical_default_survextransform_to_stepfunction

Dependencies:backportsbase64encbslibcachemcheckmatecliclustercmprskcodetoolscolorspaceDALEXdata.tablediagramdigestdoParallelevaluatefansifarverfastmapfontawesomeforeachforeignFormulafsfuturefuture.applyggplot2globalsgluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsiBreakDowningredientsisobanditeratorsjquerylibjsonlitekernelshapKernSmoothknitrlabelinglatticelavalifecyclelistenvmagrittrMASSMatrixMatrixModelsmemoisemetsmgcvmimemultcompmunsellmvtnormnlmennetnumDerivparallellypatchworkpecpillarpkgconfigplotrixpolsplineprodlimprogressrPublishquantregR6rangerrappdirsRColorBrewerRcppRcppArmadilloRcppEigenriskRegressionrlangrmarkdownrmsrpartrstudioapisandwichsassscalesshapeSparseMSQUAREMstringistringrsurvivalTH.datatibbletimeregtinytexutf8vctrsviridisviridisLitewithrxfunyamlzoo