Use this function to find either positive or negative biomarkers across multiple performance classification group matchings based on a given threshold between 0 and 1.
a matrix whose rows are vectors of average node data
differences between two groups of models based on some kind of classification
(e.g. number of TP predictions) and whose names are set in the
numeric. A number in the [0,1] interval, above which (or below its negative value) a biomarker will be registered in the returned result. Values closer to 1 translate to a more strict threshold and thus less biomarkers are found.
character. Accepted values are positive or negative.
The logic behind the biomarker selection is that if there is at least one value
in a column of the
diff.mat matrix that surpasses the threshold given, then the
corresponding node (name of the column) is return as a biomarker. This means
that for a single node, if at least one value that represents an average data
difference (for example, the average activity state difference) between any
of the given classification group comparisons is above the given threshold (or
below the negative symmetric threshold), then a positive (negative)
biomarker is reported.
a character vector that includes the node names that were found either as positive or negative.
Other biomarker functions:
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