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.
Michail Tsagris mtsagris@uoc.gr.
Michail Tsagris mtsagris@uoc.gr.
| Package: | gomp | Type: |
| Package | Version: | 1.0 |
| Date: | 2025-01-11 | License: |
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).