mdatools (version 0.7.0)

getClassificationPerformance: Calculation of classification performance parameters

Description

Calculates and returns performance parameters for classification result (e.g. number of false negatives, false positives, sensitivity, specificity, etc.).

Usage

getClassificationPerformance(c.ref, c.pred)

Arguments

c.ref

reference class values for objects (vector with numeric or text values)

c.pred

predicted class values for objects (array nobj x ncomponents x nclasses)

Value

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)

Details

The function is called automatically when a classification result with reference values is created, for example when applying a plsda or simca models.