performDaim

performDaim.matrix

performDaim.data.frame

a matrix or data frame containing the predictions.

a vector containing the true class labels. It can be a factor or character vector.

labels

a vector containing the prediction probability obtained by a model: see <code><a rd-options="" href="/link/Daim?package=Daim&version=1.1.0" data-mini-rdoc="Daim::Daim">Daim</a></code>.

prediction

thres

the cutoff value for error estimation. This can be a numeric value or a character string.
	If the <code>cutoff</code> set to:
	<code>"loob"</code> - the optimal cut-point corresponding to <code>loob</code> estimation of the sensitivity and the specificity.
	<code>"0.632"</code> - the optimal cut-point corresponding to <code>0.632</code> estimation of the sensitivity and the specificity. 
	<code>"0.632+"</code> - the optimal cut-point corresponding to <code>0.632+</code> estimation of the sensitivity and the specificity.

cutoff

a character string of the variable <code>labels</code> that defines a "positive" event.

labpos


  Perform the evaluation of predictions.


models

classif

Several functions for evaluating the accuracy of
classification models. The package provides the following
performance measures: repeated k-fold cross-validation,
0.632 and 0.632+ bootstrap estimation of the misclassification rate,
sensitivity, specificity and AUC. If an application is
computationally intensive, parallel execution can be used
to reduce the computational effort.

performDaim: Function to evaluate predictions

Description

Usage

Arguments

See Also

Examples