SWAP.GetKTSP.Result: Function for prediction followed by computing various...

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

Description

Given a kTSP classifier and data matrix and class labels, calculates the predictions and vote sums and then applies SWAP.GetKTSP.PredictionStats.

Usage

SWAP.GetKTSP.Result(classifier, inputMat, Groups, 
  classes=NULL, predictions=FALSE, decision_values=FALSE)

Arguments

classifier	a k-TSP classifier computed using SWAP.KTSP.Train or SWAP.Train.1TSP.
inputMat	is a matrix of data with rows being the features (such as gene names, if the matrix if gene expression data) and columns being the samples.
Groups	is a factor or a vector providing the phenotype class each sample belongs to. It should correspond to the order of samples given by the columns of inputMat.
classes	is a vetor of length 2 providing the two phenotype or class labels of Groups.
predictions	is a logical indicating whether to return the predictions or not.
decision_values	is a logical indicating whether to return the decision values or not.

Value

A list with items:

stats	A vector providing accuracy, sensitivity, specificity, balanced accuracy, and AUC.
roc	An ROC curve object produced by the pROC package.

Author(s)

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

References

See switchBox for the references.

See Also

SWAP.GetKTSP.PredictionStats

Examples

### Load gene expression data
data(trainingData)
data(testingData)

require(pROC)

### train 1-TSP
classifier = SWAP.Train.1TSP(matTraining, trainingGroup)

### get performance results
SWAP.GetKTSP.Result(classifier, matTesting, testingGroup)$stats

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