Hi dear R users, I am using the function errorest from the libbrary ipred to estimate the 10 fold and bootstrap classification error rate using regularized discriminat function analysis (functiopn rda from library klaR). Is it possible to set my own values for gamma and lambda? Any help will be highly appreciated! Best wishes, Felix library(klaR) library(ipred) # force predict to return class labels only mypredict.lda <- function(object, newdata) predict(object, newdata = newdata)$class # 10-fold cv of RDA for Iris data errorest(Species ~ ., data=iris, model=rda, estimator = "cv", predict= mypredict.lda) --
errorest of library iprde: specifiying parameters for regularized DA
2 messages · Felix Bach, Uwe Ligges
On 27.05.2011 11:55, Felix Bach wrote:
Hi dear R users, I am using the function errorest from the libbrary ipred to estimate the 10 fold and bootstrap classification error rate using regularized discriminat function analysis (functiopn rda from library klaR). Is it possible to set my own values for gamma and lambda? Any help will be highly appreciated! Best wishes, Felix library(klaR) library(ipred) # force predict to return class labels only mypredict.lda<- function(object, newdata) predict(object, newdata = newdata)$class # 10-fold cv of RDA for Iris data errorest(Species ~ ., data=iris, model=rda, estimator = "cv", predict= mypredict.lda)
Yes, via ... as in: errorest(Species ~ ., data=iris, model=rda, estimator = "cv", predict= mypredict.lda, gamma=0, lambda=0) Uwe Ligges
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