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Hello. I'm new to R and I'm trying to solve a classification problem. I have a training dataset of about 40,000 rows and 50 columns. When I try to train support vector machine, it gives me this error after a few seconds: Error in predict.svm(ret, xhold) : Model is empty! This is the code I use: ne_span_data <- as.matrix(read.table('ne_span.data.R.txt', header=TRUE, row.names='id')) library('e1071') svm_ne_span_model <- svm(NE_type ~ . , ne_span_data) it gives me: Error in predict.svm(ret, xhold) : Model is empt...

...e dependent variable is: Rexp. I tried using the svm.tune function as well as <_tune(svm.....), to tune the hyper parameters: gamma, epsilon and C. Since I am new to R, I am probably not using the svm.tune function properly. I am getting the following error message: Error in predict.svm(ret, xhold, decision.values=TRUE): Model is empty! May you please help me!SADAF ZAIDI [[alternative HTML version deleted]]

...uot; parameter from your `ranges` list, it works. Perhaps you should try tweaking the values you pick for your parameters. You don't even have to put it in the `tune` function to get an idea of the ranges you should use: R> m=svm(Rexp ~ ., data=retrain, epsilon=10)Error in predict.svm(ret, xhold, decision.values = TRUE) : Model is empty! See? I think if you do a bit of exploration of the parameter space, you'll get it to work. -steve On Mon, Apr 11, 2011 at 10:50 PM, Sadaf Zaidi <s.zaidi.ke at amu.ac.in> wrote: > Dear Sir, > Thanks for ur prompt reply. The details are:...

What should I do if I need to train svm() with data having same value across all rows in some columns. These must be the important features of the class and we cant exclude these columns to build up models. The error 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 -----------------------------...

...sion. My data has 5 dimensions and 400 observations. The independent variables are : Peb, Ksub, Sub, and Xtt. The dependent variable is: Rexp. I tried using the svm.tune function to tune the hyper parameters: gamma, epsilon and C. I am getting the following error message: Error in predict.svm(ret, xhold, decision.values+TRUE): Model is empty! May you please help me! SADAF ZAIDI Associate Professor Department of Aligarh Muslim University Aligarh 202002.

Hola a todos, estoy intentado entrenar un modelo SVM y me da con el valor de nu=0.1 el siguiente error Error en predict.svm(ret, xhold) : NA/NaN/Inf en llamada a una función externa (arg 8) Según varío el valor de nu a valores menores me da el mismo cuelgue. En cambio si uso valores mayores de nu el ordenador simplemente se cuelga ¿tendrá esto remedio? Uso la librería e1071 ¿existe alguna otra librería de SVM que conozcáis y...

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]]

...0, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30)), scale = c(TRUE, TRUE, FALSE, FALSE, TRUE), type = "nu-regression", kernel = "polynomial", cost = 1, nu = 0, degree = 2, gamma = 0.0009765625, coef0 = -1) debug: UseMethod("svm") Browse[1]> Error in predict.svm(ret, xhold) : NA/NaN/Inf in foreign function call (arg 9) > [[alternative HTML version deleted]]