Clustering-Based K-Nearest Neighbor Regression for Longitudinal Data
Overview
Implements the 'CKNNRLD' algorithm (Clustering-Based K-Nearest Neighbor Regression for Longitudinal Data) for improving K-Nearest Neighbor ('KNN') regression on longitudinal data through cluster-based partitioning and localized prediction. Offers enhanced computational efficiency and accuracy for high-volume longitudinal datasets. The acronym 'KNN' stands for K-Nearest Neighbor. References: Loeloe MS, Tabatabaei SM, Sefidkar R, Mehrparvar AH, Jambarsang S (2025). "Boosting K-nearest neighbor regression performance for longitudinal data through a novel learning approach." BMC Bioinformatics, 26, 232. doi:10.1186/s12859-025-06205-1.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK7 OK2026-05-29
Documentation
- Help pages
- 17
- Examples that run
- 46%6 run in a plain check · 7 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 89%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Installing CKNNRLD adds 86 packages (52 with compiled code, 82 MB of source tarballs). Heaviest: BH 14 MB, sf 9.3 MB, ggplot2 6.0 MB.
Code & Tests
Datasets
People & History
Package metadata
- First published
- 2026-05-28
- Total releases
- 4 / 1 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 5.9 KB / 1 file
- Download size
- 21 KB
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