Package: rmlnomogram 0.1.2

Herdiantri Sufriyana
rmlnomogram: Construct Explainable Nomogram for a Machine Learning Model
Construct an explainable nomogram for a machine learning (ML) model to improve availability of an ML prediction model in addition to a computer application, particularly in a situation where a computer, a mobile phone, an internet connection, or the application accessibility are unreliable. This package enables a nomogram creation for any ML prediction models, which is conventionally limited to only a linear/logistic regression model. This nomogram may indicate the explainability value per feature, e.g., the Shapley additive explanation value, for each individual. However, this package only allows a nomogram creation for a model using categorical without or with single numerical predictors. Detailed methodologies and examples are documented in our vignette, available at <https://htmlpreview.github.io/?https://github.com/herdiantrisufriyana/rmlnomogram/blob/master/doc/ml_nomogram_exemplar.html>.
Authors:
rmlnomogram_0.1.2.tar.gz
rmlnomogram_0.1.2.tar.gz(r-4.7-any)rmlnomogram_0.1.2.tar.gz(r-4.6-any)
rmlnomogram_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
rmlnomogram/json (API)
| # Install 'rmlnomogram' in R: |
| install.packages('rmlnomogram', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- nomogram_features - Nomogram features using categorical predictors
- nomogram_features2 - Nomogram features using categorical and 1 numerical predictors
- nomogram_features3 - Nomogram features using categorical predictors
- nomogram_features4 - Nomogram features using categorical and 1 numerical predictors
- nomogram_outputs - Nomogram outputs using the predicted probability of binary outcome
- nomogram_outputs2 - Nomogram outputs using the predicted probability of binary outcome
- nomogram_outputs3 - Nomogram outputs using the estimated value of numerical outcome
- nomogram_outputs4 - Nomogram outputs using the estimated value of numerical outcome
- nomogram_shaps - Nomogram SHAP values using categorical predictors and binary outcome
- nomogram_shaps2 - Nomogram SHAP values using categorical and 1 numerical predictors and binary outcome
- nomogram_shaps3 - Nomogram SHAP values using categorical predictors and numerical outcome
- nomogram_shaps4 - Nomogram SHAP values using categorical and 1 numerical predictors and numerical outcome
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:46323e9840. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 195 | ||
| source / vignettes | OK | 286 | ||
| linux-release-x86_64 | OK | 239 | ||
| wasm-release | OK | 186 |
Exports:create_nomogram
Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvminqamodelrnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpolynompurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrstatixS7scalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo