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gomp (version 1.0)

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. . 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. .

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Version

Install

install.packages('gomp')

Monthly Downloads

141

Version

1.0

License

GPL (>= 2)

Maintainer

Michail Tsagris

Last Published

January 20th, 2025

Functions in gomp (1.0)

gomp-package

The gamma-OMP Feature Selection Algorithm
Bootstrap bias correction for the performance of the cross-validation procedure

Bootstrap bias correction for the performance of the cross-validation procedure
The gamma-Orthogonal Matching Pursuit (gamma-OMP) algorithm

The gama-Orthogonal Matching Pursuit (gamma-OMP) algorithm
Generate random folds for cross-validation

Generate random folds for cross-validation
Cross-validation for gamma-Orthogonal Matching Pursuit (gamma-OMP) algorithm

Cross-validation for the gamma-Orthogonal Matching Pursuit (gamma-OMP) algorithm