Hi all,
I'm working with some data: 54 variables and a column of classes, each observation as one of a possible seven different classes: > var.can3<-lda(x=dados[,c(1:28,30:54)],grouping=dados[,55],CV=TRUE) Warning message: In lda.default(x, grouping, ...) : variables are collinear > summary(var.can3) Length Class Mode class 30000 factor numeric ### why?? I don't understand it posterior 210000 -none- numeric call 4 -none- call ## what's this? > var.can<-lda(dados[,c(1:28,30:54)],dados[,55])#porque a variavel 29 é > constante Warning message: In lda.default(x, grouping, ...) : variables are collinear > summary(var.can) Length Class Mode prior 7 -none- numeric counts 7 -none- numeric means 371 -none- numeric scaling 318 -none- numeric lev 7 -none- character svd 6 -none- numeric N 1 -none- numeric call 3 -none- call > (normalizar<-function(matriz){ n<-dim(matriz)[1]; m<-dim(matriz)[2]; > normas<-sqrt(colSums(matriz*matriz)); > matriz.normalizada<-matriz/t(matrix(rep(normas,n),m,n));return(matriz.normalizada)}) function(matriz){ n<-dim(matriz)[1]; m<-dim(matriz)[2]; normas<-sqrt(colSums(matriz*matriz)); matriz.normalizada<-matriz/t(matrix(rep(normas,n),m,n));return(matriz.normalizada)} > var.canonicas<-as.matrix(dados[,c(1:28,30:54)])%*%(normalizar(var.can$scaling)) > summary(var.canonicas) LD1 LD2 LD3 LD4 Min. :-21.942 Min. :-6.820 Min. :-10.138 Min. :-6.584 1st Qu.:-20.014 1st Qu.:-5.480 1st Qu.: -8.280 1st Qu.: 0.872 Median :-19.495 Median :-5.007 Median : -7.800 Median : 1.083 Mean :-18.827 Mean :-4.760 Mean : -7.803 Mean : 1.134 3rd Qu.:-18.975 3rd Qu.:-4.456 3rd Qu.: -7.278 3rd Qu.: 1.311 Max. : -7.886 Max. : 3.116 Max. : -1.619 Max. : 5.556 LD5 LD6 Min. :-11.083 Min. :-4.4972 1st Qu.: -1.237 1st Qu.:-1.6497 Median : -1.100 Median :-1.0909 Mean : -1.100 Mean :-0.9808 3rd Qu.: -0.957 3rd Qu.:-0.4598 Max. : 4.712 Max. : 7.5356 > I don't know wether I need to specify a training set and a testing set, I also don't know the error nor the classifier; shouldn't the lenght of class of var.can3 be 7 since I only have 7 different classes? Best regards, Pedro Marques ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.