performance.Daim: Function to evaluate predictions

In Daim: Diagnostic accuracy of classification models.

Description

Perform the evaluation of predictions.

Usage

## S3 method for class 'matrix'
performDaim(x, labels, prediction=NULL,
            thres=seq(0,1,by=0.01),
            cutoff=0.5, labpos="1", ...)
		
## S3 method for class 'data.frame'
performDaim(x, labels, prediction=NULL,
            thres=seq(0,1,by=0.01),
            cutoff=0.5, labpos="1", ...)

Arguments

x	a matrix or data frame containing the predictions.
labels	a vector containing the true class labels. It can be a factor or character vector.
prediction	a vector containing the prediction probability obtained by a model: see Daim.
thres	a numeric vector with the cutoff values.
cutoff	the cutoff value for error estimation. This can be a numeric value or a character string. If the cutoff set to: "loob" - the optimal cut-point corresponding to loob estimation of the sensitivity and the specificity. "0.632" - the optimal cut-point corresponding to 0.632 estimation of the sensitivity and the specificity. "0.632+" - the optimal cut-point corresponding to 0.632+ estimation of the sensitivity and the specificity.
labpos	a character string of the variable labels that defines a "positive" event.
...	additional parameters.

See Also

Daim, plot.Daim

Examples

  data(Daim.data1)
  (perform <- performDaim(Daim.data1$prob.oob, Daim.data1$labels, Daim.data1$prob.app))

Example output

Loading required package: parallel

Performance of the classification obtained by:

Call:
 list()
<environment: 0x7199da0>

Daim parameters: 
  est.method = obs, cutoff = 0.5.

Result: 
---------------------------------------------------------
 Error:    | .632+   |  .632    |  loob    |  apparent  |
           ----------------------------------------------
           | 0.2224  |  0.1954  |  0.2705  |  0.0663    |
---------------------------------------------------------

Daim documentation built on May 29, 2017, 9:08 a.m.