fit(eset, class="class", method = "welch.test", hparam = 0.75)
predictor
object, see predictor.object
for details.
eset
contains the expression signatures of the patients in the columns. The vector class
contains the class membership of each sample or patient. Only two-class problems are supported. The colnames of eset
are matched to the names of classifier
(if both exist).The hyperparameter hparam
describes the minimum number of samples in each class after applying shift/throw. For copa
the hyperparameter is quanilte for the definition of outliers. Typical values are 0.75 (default), 0.9, 0.95.
A nearest centroid predictor is constructed by calculating the average level ofeach feature in each of the two classes of the trainig data set.
predictor