xPierROCR: Function to assess the dTarget performance via ROC and...

Description Usage Arguments Value Note See Also Examples

View source: R/xPierROCR.r

Description

xPierROCR is supposed to assess the dTarget performance via Receiver Operating Characteristic (ROC) and Precision-Recall (PR) analysis. It requires three inputs: 1) Gold Standard Positive (GSP) targets; 2) Gold Standard Negative (GSN) targets; 3) dTarget containing predicted targets and predictive scores.

Usage

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xPierROCR(dTarget, GSP, GSN, verbose = TRUE)

Arguments

dTarget

a data frame containing dTargets along with predictive scores. It has two columns: 1st column for target, 2nd column for predictive scores (the higher the better). Alternatively, it can be an object of class "pNode" (or "sTarget" or "dTarget") from which a data frame is extracted

GSP

a vector containing Gold Standard Positives (GSP)

GSN

a vector containing Gold Standard Negatives (GSN)

verbose

logical to indicate whether the messages will be displayed in the screen. By default, it sets to TRUE for display

Value

an object of the class "dTarget", a list with following components:

Note

AUC: the area under ROC F-measure: the maximum of a harmonic mean between precision and recall along PR curve

See Also

xPierROCR

Examples

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RData.location <- "http://galahad.well.ox.ac.uk/bigdata"
## Not run: 
dTarget <- xPierROCR(dTarget, GSP, GSN)
gp <- xPredictCompare(dTarget$pPerf)

## End(Not run)

Pi documentation built on Nov. 26, 2020, 2:01 a.m.