errorRate: This function calculates the error rates for the different EM...

In RobustEM: Robust Mixture Modeling Fitted via Spatial-EM Algorithm for Model-Based Clustering and Outlier Detection

Description

This function uses different criteria to measure the accuracy of predicted labels with respect to the true labels.

Usage

errorRate(actual, predicted, beta=1)

Arguments

actual	This is a vector that represents the actual true class labels.
predicted	This is the predicted cluster returned by the EM algorithm
beta	This is a parameter of beta used for the F-measure. The default is 1 which correpondes to the balanced F-measure.

Value

FPR	Represents the computed False Positive Rate
FNR	Represents the computed False Negative Rate
RI	Represents the computed Rand Index
F	Represents the computed F-Measure

Warning

This function is dependent on the true and predicted clusters having the same levels.

See Also

matchCluster

Examples

## Not run: 
  true<-c("a","b","a","a","a")
   predicted<-c("a","b","b","a","a")
   errorRate(true,predicted)

## End(Not run)

RobustEM documentation built on April 14, 2017, 10:05 a.m.