Calculates and returns performance parameters for classification result (e.g. number of false negatives, false positives, sensitivity, specificity, etc.).
getClassificationPerformance(c.ref, c.pred)reference class values for objects (vector with numeric or text values)
predicted class values for objects (array nobj x ncomponents x nclasses)
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 |
sensitivity values (nclasses x ncomponents) |
$specificity |
specificity values (nclasses x ncomponents) |
$sensitivity |
misclassified ratio values (nclasses x ncomponents) |
The function is called automatically when a classification result with reference values is
created, for example when applying a plsda or simca models.