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SVM

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formula <- as.formula(factor(DIABETE2) ~ . ); svm.tune <- tune.svm(formula, data = train.set, gamma = 10^(-3:0), cost = 10^(-1:1)); svm.model <- svm(formula, data = train.set, kernel = "linear", gamma = svm.tune$best.parameters$gamma, cost = svm.tune$best.parameters$cost);

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Confusion matrix

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train.pred <- predict(svm.model, train.set); test.pred <- predict(svm.model, test.set); svm.table <- table(pred = test.pred, true = test.result); print(svm.table);