Calculate Error Rates for Linear Discriminant Model
Given an lda model object, calculate training set error, leave-one-out cross-validation error, and test set error.
ldaErr(train.lda, train, test, group = "type")
train.lda
: Fitted lda model object.train
: Training set data frame.test
: Test set data frame.group
: Factor that identifies groups in training data.Vector that holds leave-one-out, training, and test error rates
## Not run: data(spam, package='kernlab') spam[,-58] <- scale(spam[,-58]) nr <- sample(1:nrow(spam)) spam01 <- spam[nr[1:3601],] ## Use for training, spam2 <- spam[nr[3602:4601],] ## Test spam01.lda <- lda(type~., data=spam01) ldaRates <- ldaErr(train.lda=spam01.lda, train=spam01, test=spam2, group="type") ## End(Not run)
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