HI, GUYS, I used the following codes to run SVM and get prediction on new data set hh.
dim(all_h) [1] 2034 24 dim(hh) # it contains all the variables besides the variables in all_h data set. [1] 640 415 require(e1071) svm.tune<-tune(svm, as.factor(out) ~ ., data=all_h, ranges=list(gamma=2^(-5:5), cost=2^(-5:5)))# find the best parameters. bestg<-svm.tune$best.parameters[[1]] bestc<-svm.tune$best.parameters[[2]] svm.fit<-svm(as.factor(out) ~ ., data=all_h, method="C-classification", kernel="radial", probability = TRUE, cost=bestc, gamma=bestg, cross=10) # model fitting svm.pred<-predict(svm.fit, hh, decision.values = TRUE, probability = TRUE) # find the probability. * Error in matrix(ret$dec, nrow = nrow(newdata), byrow = TRUE, dimnames = list(rowns, : invalid 'ncol' value (too large or NA)* > head(all_h) DD HK HQ IL LP NE NP TA TP WA WC 1 0.00543 0 0 0.00815 0.00272 0.00543 0.00000 0.00000 0.00000 0.00000 0 3 0.00000 0 0 0.00890 0.00890 0.00712 0.00534 0.00000 0.00890 0.00178 0 4 0.00448 0 0 0.00448 0.00299 0.00448 0.00149 0.00299 0.00000 0.00149 0 5 0.00312 0 0 0.00467 0.00467 0.00000 0.00156 0.00467 0.00312 0.00467 0 6 0.00587 0 0 0.02053 0.00587 0.00000 0.00293 0.00587 0.00293 0.00000 0 7 0.00000 0 0 0.02422 0.00346 0.00000 0.00346 0.00346 0.00000 0.00346 0 WD WG WN YW acid_per base_per charge_per 1 0.00000 0.00000 0.00000 0.00000 0.14402174 0.12228261 0.019021739 3 0.00178 0.00178 0.00534 0.00178 0.12277580 0.09252669 0.016014235 4 0.00149 0.00448 0.00448 0.00000 0.16591928 0.11509716 0.022421525 5 0.00000 0.00156 0.00000 0.00156 0.13084112 0.10903427 0.009345794 6 0.00293 0.00000 0.00000 0.00000 0.07038123 0.08797654 0.002932551 7 0.00000 0.00346 0.00000 0.00346 0.05536332 0.08650519 0.010380623 hydrophob_per polar_per num_cell num_genes position out 1 0.3804348 0.1929348 1 4 1 0 3 0.3540925 0.2508897 1 4 3 0 4 0.3393124 0.2032885 1 4 4 1 5 0.3753894 0.2305296 2 7 1 0 6 0.4868035 0.1964809 2 7 2 0 7 0.4878893 0.1522491 2 7 3 0 > quantile(hh$HK) 0% 25% 50% 75% 100% 0.00000 0.00000 0.00000 0.00000 0.02703 > quantile(hh$HQ) 0% 25% 50% 75% 100% 0.000 0.000 0.000 0.000 0.025 > quantile(hh$WC) 0% 25% 50% 75% 100% 0.00000 0.00000 0.00000 0.00000 0.01266 Can someone give some suggestions? Thanks! -- Sincerely, Changbin -- [[alternative HTML version deleted]] ______________________________________________ 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.