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

Description Usage Arguments Value Author(s) References See Also

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

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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 bahman.afsari@gmail.com, Luigi Marchionni marchion@jhu.edu, Wikum Dinalankara wdinala1@jhmi.edu

References

See switchBox for the references.

See Also

SWAP.Kby.Ttest, SWAP.MakeTSPTable


marchion/switchBox documentation built on May 9, 2019, 4:07 p.m.