Package: FuzzyLogit 0.1.1

Md Faruk Hasan

FuzzyLogit: Fuzzy Logistic Regression

Fits logistic regression models in which the binary response is represented by a triangular fuzzy number rather than an exact crisp label, allowing uncertainty in class membership to be encoded directly in the outcome. Model parameters are estimated using the Fuzzy Least Squares approach of Diamond (1988) <doi:10.1016/0020-0255(88)90047-3>, following the integrated fuzzy logistic regression method of Yapici Pehlivan and Sahin (2018) <https://dergipark.org.tr/en/pub/jssa/issue/37877/437725>. Provides fitting, prediction, classification, cross-validation, and diagnostic plotting methods, along with tools for comparing model behaviour across different assumed levels of label uncertainty.

Authors:Md Faruk Hasan [aut, cre], Azizur Rahman [aut]

FuzzyLogit_0.1.1.tar.gz
FuzzyLogit_0.1.1.zip(r-4.7-any)FuzzyLogit_0.1.1.zip(r-4.6-any)
FuzzyLogit_0.1.1.tar.gz(r-4.7-any)FuzzyLogit_0.1.1.tar.gz(r-4.6-any)
FuzzyLogit_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
FuzzyLogit/json (API)

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 412 downloads 12 exports 30 dependencies

Last updated from:795946b75c. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK112
source / vignettesOK149
linux-releaseOK116
windows-develOK77
windows-releaseOK80
wasm-releaseOK110

Exports:case.namesclassifycompare_cv_resultscompare_fuzzy_modelscv.fuzzy_logitfuzzy_logitis.fuzzy_logitplot_binned_residualsplot_fuzzy_membershipplot_leverageplot_pearson_residualsplot_scale_location

Dependencies:clicpp11dplyrfarvergenericsggplot2gluegtableisobandlabelinglifecyclemagrittrMASSpillarpkgconfigpurrrR6RColorBrewerrlangS7scalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
UCI Breast Cancer Wisconsin Datasetbreast_cancer
Extract case names from fuzzy_logit modelcase.names
Classify Observations Using a Fuzzy Logistic Regression Modelclassify classify.fuzzy_logit print.classify.fuzzy_logit summary.classify.fuzzy_logit
Extract coefficients from fuzzy_logit modelcoef.fuzzy_logit
Extract coefficients from fuzzy_logit model (alias)coefficients.fuzzy_logit
Compare Multiple Cross-Validation Resultscompare_cv_results
Compare Multiple Fuzzy Logit Models with Different Mu Valuescompare_fuzzy_models
Confidence intervals for fuzzy_logit model parametersconfint.fuzzy_logit
Cross-Validation for Fuzzy Logistic Regressioncv.fuzzy_logit
Deviance for fuzzy_logit modeldeviance.fuzzy_logit
Extract residual degrees of freedomdf.residual.fuzzy_logit
Extract fitted values from fuzzy_logit modelfitted.fuzzy_logit
Extract formula from fuzzy_logit modelformula.fuzzy_logit
Fuzzy Logistic Regression with Customizable Membership Functionsfuzzy_logit
Check if object is a fuzzy_logit modelis.fuzzy_logit
Log-likelihood for fuzzy_logit modellogLik.fuzzy_logit
Extract model frame from fuzzy_logit modelmodel.frame.fuzzy_logit
Extract model matrix from fuzzy_logit modelmodel.matrix.fuzzy_logit
Extract number of observations from fuzzy_logit modelnobs.fuzzy_logit
Plot Binned Residuals for a Fuzzy Logistic Regression Modelplot_binned_residuals
Visualize Fuzzy Membership Functionsplot_fuzzy_membership
Residuals vs. Leverage Plot for a Fuzzy Logistic Regression Modelplot_leverage
Plot Pearson Residuals vs. Fitted Probabilitiesplot_pearson_residuals
Scale-Location Plot for a Fuzzy Logistic Regression Modelplot_scale_location
Plot diagnostic plots for fuzzy_logit modelplot.fuzzy_logit
Predict method for fuzzy_logit modelspredict.fuzzy_logit
Print Cross-Validation Resultsprint.cv.fuzzy_logit
Print method for fuzzy_logit objectsprint.fuzzy_logit
Print method for fuzzy_logit_comparisonprint.fuzzy_logit_comparison
Print method for summary.fuzzy_logit objectsprint.summary.fuzzy_logit
Extract residuals from fuzzy_logit modelresiduals.fuzzy_logit
Summarise Cross-Validation Resultssummary.cv.fuzzy_logit
Summary method for fuzzy_logit objectssummary.fuzzy_logit
Extract terms from fuzzy_logit modelterms.fuzzy_logit
Update fuzzy_logit modelupdate.fuzzy_logit
Extract variable names from fuzzy_logit modelvariable.names.fuzzy_logit
Variance-covariance matrix for fuzzy_logit modelvcov.fuzzy_logit