T1FF
Type-1 Fuzzy Functions for Classification, Regression, and Forecasting
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | T1FF_0.1.0.tar.gz |
165.3 KiB |
0.1.0 |
rolling linux/noble R-4.5 | T1FF_0.1.0.tar.gz |
165.3 KiB |
0.1.0 |
rolling source/ R- | T1FF_0.1.0.tar.gz |
60.2 KiB |
0.1.0 |
latest linux/jammy R-4.5 | T1FF_0.1.0.tar.gz |
165.3 KiB |
0.1.0 |
latest linux/noble R-4.5 | T1FF_0.1.0.tar.gz |
165.3 KiB |
0.1.0 |
latest source/ R- | T1FF_0.1.0.tar.gz |
60.2 KiB |
0.1.0 |
2026-04-23 source/ R- | T1FF_0.1.0.tar.gz |
0 B |