rocc: ROC based classification
Functions for a classification method based on receiver
operating characteristics (ROC). Briefly, features are selected
according to their ranked AUC value in the training set. The
selected features are merged by the mean value to form a
metagene. The samples are ranked by their metagene value and
the metagene threshold that has the highest accuracy in
splitting the training samples is determined. A new sample is
classified by its metagene value relative to the threshold. In
the first place, the package is aimed at two class problems in
gene expression data, but might also apply to other problems.
||Martin Lauss <martin.lauss at med.lu.se>
||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
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