cancerclass: Development and validation of diagnostic tests from high-dimensional molecular data

The classification protocol starts with a feature selection step and continues with nearest-centroid classification. The accurarcy of the predictor can be evaluated using training and test set validation, leave-one-out cross-validation or in a multiple random validation protocol. Methods for calculation and visualization of continuous prediction scores allow to balance sensitivity and specificity and define a cutoff value according to clinical requirements.

Package details

AuthorJan Budczies, Daniel Kosztyla
Bioconductor views Cancer Classification Microarray Visualization
MaintainerDaniel Kosztyla <[email protected]>
LicenseGPL 3
Package repositoryView on Bioconductor
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cancerclass documentation built on Nov. 1, 2018, 3:21 a.m.