Hi all, I'm using SVM to classify data (2 classes) and I get strange results :
> model = svm(x, y, probability = TRUE) > pred = predict(model, x, decision.values = TRUE, probability = FALSE) > table(pred,y) y pred ctl nuc ctl 82 3 nuc 5 84 > pred 1 2 3 4 5 6 7 8 .... nuc nuc nuc nuc nuc nuc nuc ctl .... And now, with probabities computation : > pred = predict(model, x, decision.values = TRUE, probability = TRUE) > table(pred,y) y pred ctl nuc ctl 7 84 nuc 80 3 > pred 1 2 3 4 5 6 7 8 .... ctl ctl ctl ctl ctl ctl ctl nuc ... However, model, x, and y didn't change !! Also, decision.values didn't change : nuc/ctl 1 0.505289854 2 0.265975135 3 0.863270144 4 0.354181677 5 0.868119168 6 0.702989607 7 0.206018067 8 -0.271452937 -> ctl is correct ! .... Is it a bug ? Could you explain the difference ? Best regards, charles -- Charles Hébert DYnamique et Organisation des GENomes, Laboratoire de Génétique Moléculaire, CNRS UMR 8541 Ecole Normale Supérieure 46, rue d'Ulm 75005 Paris, France [[alternative HTML version deleted]]
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