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...I am getting is: Error in predict.svm(ret, xhold) : Model is empty! In addition: Warning message: In svm.default(datatrain, classtrain) : Variable(s) 'F112' and 'F113'.... [... truncated] Is there any way to overcome this problem? Any suggestions would be highly helpful. Regards Soumyadeep --------------------------------- [[alternative HTML version deleted]]

...a matrix which I want to make some 3D plots using R. There is some functions for instance hist() for 2D plots, but I cant find any function for 3D plots. Is there any function available in R for 3D plots? If so, is there any documention available on internet so that I can go through. With regards, Soumyadeep

My data looks like: A,B,C,D,Class 1,2,0,2,cl1 1,5,1,9,cl1 3,2,1,2,cl2 7,2,1,2,cl2 2,2,1,2,cl2 1,2,1,5,cl2 0,2,1,2,cl2 4,2,1,2,cl2 3,5,1,2,cl2 3,2,12,3,cl2 3,2,4,2,cl2 **The steps followed are: trainfile <- read.csv("TrainFile",head=TRUE) datatrain <- subset(trainfile,select=c(-Class)) classtrain <- (subset(trainfile,select=Class)) rf <- randomForest(datatrain, classtrain)

What should I do if I need to train svm() with data having same value in number of columns. These must be the deterministic features for the class. Is there anyway to over come this trouble? Regards --------------------------------- [[alternative HTML version deleted]]

Hi, I am trying to train svm with some training data of about 4000 rows and 4000 columns. While running svm function I am ending up with the following error. trainfile <- read.csv('0_train_0016435.csv',head=TRUE,na.strings = "NULL") datatrain <- subset(trainfile,select=c(-Class)) model <- svm(datatrain, kernel="radial") Error in FUN(newX[, i], ...) :

While trying to train randomForest with my dataset, I am ending up with the following error Error in randomForest.default(datatrain, classtrain) : length of response must be the same as predictors My data looks like: A,B,C,D,Class 1,2,1,2,cl1 1,2,1,2,cl1 3,2,1,2,cl2 3,2,1,2,cl2 3,2,1,2,cl2 3,2,1,2,cl2 3,2,1,2,cl2 3,2,1,2,cl2 3,2,1,2,cl2 3,2,12,3,cl2 3,2,1,2,cl2 Actual dataset has around 4000