RobustEM (version 1.0)

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

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)