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. María Gabriela Cendoya
Magíster en Biometría
Profesor Adjunto
Cátedra de Estadística y Diseño
Facultad de Ciencias Agrarias
Universidad Nacional de Mar del Plata
______________________________
----- Original Message -----
From: "BostonR" <dp...@capitaliq.com>
To: <r-help@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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PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
