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).


[Package gomp version 1.0 Index]