predomics/predomicspkg: Interpretable Prediction in Omics Data
The predomics package offers access to a novel framework implementing several heuristics that allow finding sparse and interpretable models in large datasets. These models are efficient and adopted for classification and regression in metagenomics and other commensurable datasets. We introduce the BTR (BIN, TER, RATIO) languages that describe different types of associations between variables. Moreover, in the same framework we implemented several state-of-the-art methods (SOTA) including RF, ENET and SVM.
Getting started
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Package details |
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| Author | Edi Prifti, Jean-Daniel Zucker, Yann Chevaleyre, Blaise Hanczar, Eugeni Belda, Lucas Robin, Shasha Cui, Magali Cousin Thorez, Youcef Sklab, Gaspar Roy |
| Maintainer | Edi Prifti <edi.prifti@ird.fr> |
| License | GPL-3 + file LICENSE |
| Version | 1.3.1 |
| URL | https://predomics.github.io/predomicspkg/ |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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