Provides a genetic algorithm for finding variable subsets in high dimensional data with high prediction performance. The genetic algorithm can use ordinary least squares (OLS) regression models or partial least squares (PLS) regression models to evaluate the prediction power of variable subsets. By supporting different cross-validation schemes, the user can fine-tune the tradeoff between speed and quality of the solution.
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Summary
Provides a genetic algorithm for finding variable subsets in high dimensional data with high prediction performance. The genetic algorithm can use ordinary least squares (OLS) regression models or partial least squares (PLS) regression models to evaluate the prediction power of variable subsets. By supporting different cross-validation schemes, the user can fine-tune the tradeoff between speed and quality of the solution.
Information Last Updated
Apr 22, 2025 at 15:32
License
GPL-2
Total Downloads
3
Platforms