Type-1 Fuzzy Functions for Classification, Regression, and Forecasting R package T1FF version 0.1.0 Fits Type-1 Fuzzy Function models for binary classification, numeric regression, and time-series forecasting with user-supplied temporal predictors. The package combines fuzzy C-means memberships, nonlinear membership transformations, cluster-specific linear or support vector machine models, and membership-weighted predictions. It also provides model evaluation, validation, K-fold and stratified K-fold tuning, and repeated nested cross-validation with task-appropriate metrics. The regression workflow can be used for forecasting when temporal dependence is represented by lagged or seasonal predictors and assessment partitions preserve chronological order. Software Depends: R (>= 4.1.0) Imports: e1071, kernlab, stats, utils Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Nihat Tak <nihattak@gmail.com> Comprehensive R Archive Network (CRAN) Nihat Tak [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=T1FF/LICENSE) 2026-09-15 application/tgz https://CRAN.R-project.org/package=T1FF doi:10.32614/CRAN.package.T1FF