Hi Steve I am facing a little problem in predict function which is I think mismatch of dimension. Infacted area is covered by ***. svm = function() { library(RODBC) # load RODBC library for database access channel = odbcConnect("demo_dsn", "sa", "1234") # connecting to the database with the dabtabase data = sqlQuery(channel, "SELECT top 100 * FROM [Demographics].[dbo].[CHA_Training]") odbcClose(channel) # close the database connection index = 1:nrow(data) # getting a vector of same size as data sample_index <- sample(index, length(index) / 3) # samples of the above vector training <- data[-sample_index, ] # 2/3 training data validation <- data[sample_index, ] # 1/3 test data x = training[, length(training)] # seperating class labels model.ksvm = ksvm(x, data = training, kernel = "rbfdot", kpar= list(sigma = 0.05), C = 5, cross = 3) # train data through SVM ******************************************************************* Problamisitc area: prSV = predict(model.ksvm, validation[, -length(validation)], type = "decision") # validate data Error: Error in .local(object, ...) : test vector does not match model ! Notes: If I modified the predict function as "prSV = predict(model.ksvm, validation[, length(validation)], type = "decision")" then it works but its not correct. ***************************************************************** table(prSV, validation[, length(validation)]) # draw table } Thanks Abbas
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