SWAP.GetKTSP.PredictionStats: Function for computing various performance measures related...

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/exportedFuncs.R

Description

Given a list of predicted labels and true labels, provides accuracy, sensitivity, specificity, balanced accuracy (i.e. (sensitivity+specificity)/2 ), and AUC if decision values are given.

Usage

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SWAP.GetKTSP.PredictionStats(predictions, truth, classes=NULL, 
  decision_values=NULL)

Arguments

predictions

is a vector or factor of predicted classes.

truth

is a vector or factor of the true class labels.

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.

decision_values

is a vector providing the decision values (such as sum of votes from a k-TSP classifier). Will be used to compute AUC if provided.

Value

A vector providing accuracy, sensitivity, specificity, and balanced accuracy , and if decision_values is prodvided, area under the ROC curve (AUC).

Author(s)

Bahman Afsari [email protected], Luigi Marchionni [email protected], Wikum Dinalankara [email protected]

References

See switchBox for the references.

See Also

SWAP.KTSP.Classify

Examples

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

### train 1-TSP
classifier = SWAP.Train.1TSP(matTraining, trainingGroup)
predictions = SWAP.KTSP.Classify(matTesting, classifier)

### get performance results
SWAP.GetKTSP.PredictionStats(predictions, testingGroup)

switchBox documentation built on Nov. 1, 2018, 2:46 a.m.