SWAP.Kby.Measurement: K selection for a kTSP classifier.

In switchBox: Utilities to train and validate classifiers based on pair switching using the K-Top-Scoring-Pair (KTSP) algorithm

Description

SWAP.Kby.Measurement can be supplied to a kTSP classifier training function to select an optimal k by adding top-scoring pairs to maximize a given measurement such as accuracy or sensitivitiy over the training data.

Usage

SWAP.Kby.Measurement(inputMat, phenoGroup, 
  scoreTable, classes, krange, 
  k_opts=list(disjoint=TRUE, measurement="auc")

Arguments

inputMat	is a numerical matrix containing the measurements (e.g., gene expression data) to be used to build the K-TSP classifier.
phenoGroup	is a factor with two levels containing the phenotype information used to train the K-TSP classifier.
scoreTable	a data frame output of SWAP.MakeTSPTable containing TSPs and the accuracy of individuals pairs over the training data.
classes	is a character vector of length 2 providing the phenotype class labels (case followed by control). If NULL, the levels of phenoGroup will be taken as the labels.
krange	an integer (or a vector of integers) defining the candidate number of Top Scoring Pairs (TSPs) from which the algorithm chooses to build the final classifier.
k_opts	is a list of additional variables: disjoint is a logical indicating whether the selected pairs should be disjoint (i.e. features not repeated), and measurement is the given measurement to be maximized: it can be accuracy, sensitivity, specificity or auc.

Value

A vector of indices of length k indicating which pairs from scoreTable should be selected.

Author(s)

Bahman Afsari [e-mail], Luigi Marchionni [e-mail], Wikum Dinalankara [e-mail]

References

See switchBox for the references.

See Also

SWAP.Kby.Ttest, SWAP.MakeTSPTable

switchBox documentation built on Nov. 8, 2020, 5:43 p.m.