LDA Precdict - Seems to be predicting on the Training Data
This is not an explanation but it gives you a solution, Instead of using lda with a formula do it by giving the variables and the classification factor as arguments, base on your example and data: outOfSample <- myDat[11:16,] train <- myDat[1:10,] outOfSample <- outOfSample[,3:5] train2 <- train[,3:5] fit <- lda(train2,train$c1) forecast <- predict(fit,outOfSample)$class length(forecast) [1] 6 Seems that the problem arise when predict.lda works on lda fit applied to a formula class object. Hope this help, Gabriela. ______________________________ Lic. Mar?a Gabriela Cendoya Mag?ster en Biometr?a Profesor Adjunto C?tedra de Estad?stica y Dise?o Facultad de Ciencias Agrarias Universidad Nacional de Mar del Plata ______________________________ ----- Original Message ----- From: "BostonR" <dpope at capitaliq.com> To: <r-help at r-project.org> Sent: Tuesday, October 20, 2009 11:31 AM Subject: [R] LDA Precdict - Seems to be predicting on the Training Data
When I import a simple dataset, run LDA, and then try to use the model to forecast out of sample data, I get a forecast for the training set not the out of sample set. Others have posted this question, but I do not see the answers to their posts. Here is some sample data: Date Names v1 v2 v3 c1 1/31/2009 Name1 0.714472361 0.902552278 0.783353694 a 1/31/2009 Name2 0.512158919 0.770451596 0.111853346 a 1/31/2009 Name3 0.470693282 0.129200065 0.800973877 a 1/31/2009 Name4 0.24236898 0.472219638 0.486599763 b 1/31/2009 Name5 0.785619735 0.628511593 0.106868172 b 1/31/2009 Name6 0.718718387 0.697257275 0.690326648 b 1/31/2009 Name7 0.327331186 0.01715109 0.861421706 c 1/31/2009 Name8 0.632011743 0.599040196 0.320741634 c 1/31/2009 Name9 0.302804404 0.475166304 0.907143632 c 1/31/2009 Name10 0.545284813 0.967196462 0.945163717 a 1/31/2009 Name11 0.563720418 0.024862018 0.970685281 a 1/31/2009 Name12 0.357614427 0.417490445 0.415162276 a 1/31/2009 Name13 0.154971203 0.425227967 0.856866993 b 1/31/2009 Name14 0.935080173 0.488659307 0.194967973 a 1/31/2009 Name15 0.363069339 0.334206603 0.639795596 b 1/31/2009 Name16 0.862889297 0.821752532 0.549552875 a Attached is the code: myDat <-read.csv(file="f:\\Systematiq\\data\\TestData.csv", header=TRUE,sep=",") myData <- data.frame(myDat) length(myDat[,1]) train <- myDat[1:10,] outOfSample <- myDat[11:16,] outOfSample <- (cbind(outOfSample$v1,outOfSample$v2,outOfSample$v3)) outOfSample <-data.frame(outOfSample) length(train[,1]) length(outOfSample[,1]) fit <- lda(train$c1~train$v1+train$v2+train$v3) forecast <- predict(fit,outOfSample)$class length(forecast)##### I am expecting this to be same as lengthoutOfSample[,1]), which is 6 Output: length(forecast)##### I am expecting this to be same as lengthoutOfSample[,1]), which is 6 [1] 10 -- View this message in context: http://www.nabble.com/LDA-Precdict---Seems-to-be-predicting-on-the-Training-Data-tp25976178p25976178.html Sent from the R help mailing list archive at Nabble.com.
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