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:Herdiantri Sufriyana [aut, cre], Emily Chia-Yu Su [aut]

rmlnomogram_0.1.2.tar.gz
rmlnomogram_0.1.2.tar.gz(r-4.5-noble)rmlnomogram_0.1.2.tar.gz(r-4.4-noble)
rmlnomogram_0.1.2.tgz(r-4.4-emscripten)
rmlnomogram.pdf |rmlnomogram.html
rmlnomogram/json (API)

# Install 'rmlnomogram' in R:
install.packages('rmlnomogram', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • 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.

2.70 score 1 exports 68 dependencies

Last updated 6 days agofrom:46323e9840. Checks:2 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 08 2025
R-4.5-linuxOKJan 08 2025

Exports:create_nomogram

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfansifarverFormulagenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpolynompurrrquantregR6RColorBrewerRcppRcppEigenrlangrstatixscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

Machine Learning Nomogram Exemplar

Rendered fromml_nomogram_exemplar.Rmdusingknitr::rmarkdownon Jan 08 2025.

Last update: 2025-01-08
Started: 2025-01-08