Signature discovery from omics data
Feature selection is critical in omics data analysis to extract restricted and meaningful molecular signatures from complex and high-dimension data, and to build robust classifiers. This package implements a method to assess the relevance of the variables for the prediction performances of the classifier. The approach can be run in parallel with the PLS-DA, Random Forest, and SVM binary classifiers. The signatures and the corresponding 'restricted' models are returned, enabling future predictions on new datasets.
System | Target | Derivation | Build status |
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x86_64-linux | /gnu/store/sb2yw4l80ijy6yzxwwxcriinhasild2k-r-biosigner-1.14.4.drv | ||
mips64el-linux | /gnu/store/vxy2avr17mlpmga1na4h1fz4jxs26aj5-r-biosigner-1.14.4.drv | ||
i686-linux | /gnu/store/p7201hvnccx37sb924l0b0y3zgji812g-r-biosigner-1.14.4.drv | ||
i586-gnu | /gnu/store/5mczdv99djhb20ib28gx2a91z4qhcq2p-r-biosigner-1.14.4.drv | ||
armhf-linux | /gnu/store/773d14jvmmkk04mdm3d94d0w8qd6kls0-r-biosigner-1.14.4.drv | ||
aarch64-linux | /gnu/store/ygsz8ml564937xd7zys7g3pj42yp2zbz-r-biosigner-1.14.4.drv |
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description Validate package descriptions | use @code or similar ornament instead of quotes |