gomp-package {gomp} | R Documentation |
The gamma-OMP Feature Selection Algorithm
Description
The gamma-Orthogonal Matching Pursuit (gamma-OMP) is a recently suggested modification of the OMP feature selection algorithm for a wide range of response variables. The package offers many alternative regression models, such linear, robust, survival, multivariate etc., including k-fold cross-validation. References: Tsagris M., Papadovasilakis Z., Lakiotaki K. and Tsamardinos I. (2018). "Efficient feature selection on gene expression data: Which algorithm to use?" BioRxiv. <doi:10.1101/431734>. Tsagris M., Papadovasilakis Z., Lakiotaki K. and Tsamardinos I. (2022). "The gamma-OMP algorithm for feature selection with application to gene expression data". IEEE/ACM Transactions on Computational Biology and Bioinformatics 19(2): 1214–1224.
Details
Package: | gomp |
Type: | Package |
Version: | 1.0 |
Date: | 2025-01-11 |
License: | GPL-2 |
Maintainers
Michail Tsagris mtsagris@uoc.gr.
Author(s)
Michail Tsagris mtsagris@uoc.gr.
References
Tsagris M., Papadovasilakis Z., Lakiotaki K. and Tsamardinos I. (2018). Efficient feature selection on gene expression data: Which algorithm to use? BioRxiv.
Tsagris M., Papadovasilakis Z., Lakiotaki K. and Tsamardinos I. (2022). The \gamma
-OMP algorithm for feature selection with application to gene expression data". IEEE/ACM Transactions on Computational Biology and Bioinformatics 19(2): 1214–1224.
Alharbi N. (2024). Variable selection with time-to-event data: Cox or Weibull regression? Communications in Statistics: Case Studies, Data Analysis and Applications (accepted for publication).