Calculates and returns performance parameters for classification result (e.g. number of false negatives, false positives, sn, specificity, etc.).
classres.getPerformance(c.ref, c.pred)Returns a list with following fields:
$fn | number of false negatives (nclasses x ncomponents) |
$fp | number of false positives (nclasses x ncomponents) |
$tp | number of true positives (nclasses x ncomponents) |
$sensitivity | sn values (nclasses x ncomponents) |
$specificity | specificity values (nclasses x ncomponents) |
$specificity | ms ratio values (nclasses x ncomponents) |
reference class values for objects (vector with numeric or text values)
predicted class values for objects (array nobj x ncomponents x nclasses)
The function is called automatically when a classification result with reference values is
created, for example when applying a plsda or simca models.