MAINT.Data (version 2.7.1)

ConfMat: Confussion Matrices for classification results

Description

‘ConfMat’ creates confussion matrices from two factor describing, respectively, original classes and predicted classification results

Usage

ConfMat(origcl, predcl, otp=c("absandrel","abs","rel"), dec=3)

Value

When argument ‘otp’ is set to “absandrel” (default), a list with two confusion matrices, respectively with absolute and relative frequencies. When argument ‘otp’ is set to “abs” a confusion matrix with absolute frequencies, and when argument ‘otp’ is set to “rel” a confusion matrix with relative frequencies.

Arguments

origcl

A factor describing the original classes.

predcl

A factor describing the predicted classes.

otp

A string describing the output to be displayed and returned. Alternatives are “absandrel” for two confusion matrices, respectively with absolute and relative frequencies, “abs” for a confusion matrix with absolute frequencies, and “rel” for a confusion matrix relative frequencies.

dec

The number of decimal digits to display in matrices of relative frequencies.

Author

A. Pedro Duarte Silva

See Also

lda, qda, snda, Roblda, Robqda, DACrossVal

Examples

# Create an Interval-Data object containing the intervals for 899 observations 
# on the temperatures by quarter in 60 Chinese meteorological stations.

ChinaT <- IData(ChinaTemp[1:8],VarNames=c("T1","T2","T3","T4"))

#Linear Discriminant Analysis

ChinaT.lda <- lda(ChinaT,ChinaTemp$GeoReg)
ldapred <- predict(ChinaT.lda,ChinaT)$class

# lda resubstitution confusion matrix

ConfMat(ChinaTemp$GeoReg,ldapred)

#Quadratic Discriminant Analysis

ChinaT.qda <- qda(ChinaT,ChinaTemp$GeoReg)
qdapred <- predict(ChinaT.qda,ChinaT)$class

# qda resubstitution confusion matrix

ConfMat(ChinaTemp$GeoReg,qdapred)