=== svm linear === Confusion Matrix and Statistics Reference Prediction 1 2 3 1 11 1 0 2 0 13 0 3 0 0 9 Overall Statistics Accuracy : 0.9706 95% CI : (0.8467, 0.9993) No Information Rate : 0.4118 P-Value [Acc > NIR] : 3.92e-12 Kappa : 0.9553 Mcnemar's Test P-Value : NA Statistics by Class: Class: 1 Class: 2 Class: 3 Sensitivity 1.0000 0.9286 1.0000 Specificity 0.9565 1.0000 1.0000 Pos Pred Value 0.9167 1.0000 1.0000 Neg Pred Value 1.0000 0.9524 1.0000 Prevalence 0.3235 0.4118 0.2647 Detection Rate 0.3235 0.3824 0.2647 Detection Prevalence 0.3529 0.3824 0.2647 Balanced Accuracy 0.9783 0.9643 1.0000 === svm rbf === Confusion Matrix and Statistics Reference Prediction 1 2 3 1 11 1 0 2 0 13 0 3 0 0 9 Overall Statistics Accuracy : 0.9706 95% CI : (0.8467, 0.9993) No Information Rate : 0.4118 P-Value [Acc > NIR] : 3.92e-12 Kappa : 0.9553 Mcnemar's Test P-Value : NA Statistics by Class: Class: 1 Class: 2 Class: 3 Sensitivity 1.0000 0.9286 1.0000 Specificity 0.9565 1.0000 1.0000 Pos Pred Value 0.9167 1.0000 1.0000 Neg Pred Value 1.0000 0.9524 1.0000 Prevalence 0.3235 0.4118 0.2647 Detection Rate 0.3235 0.3824 0.2647 Detection Prevalence 0.3529 0.3824 0.2647 Balanced Accuracy 0.9783 0.9643 1.0000 === random forest === Confusion Matrix and Statistics Reference Prediction 1 2 3 1 11 1 0 2 0 13 0 3 0 0 9 Overall Statistics Accuracy : 0.9706 95% CI : (0.8467, 0.9993) No Information Rate : 0.4118 P-Value [Acc > NIR] : 3.92e-12 Kappa : 0.9553 Mcnemar's Test P-Value : NA Statistics by Class: Class: 1 Class: 2 Class: 3 Sensitivity 1.0000 0.9286 1.0000 Specificity 0.9565 1.0000 1.0000 Pos Pred Value 0.9167 1.0000 1.0000 Neg Pred Value 1.0000 0.9524 1.0000 Prevalence 0.3235 0.4118 0.2647 Detection Rate 0.3235 0.3824 0.2647 Detection Prevalence 0.3529 0.3824 0.2647 Balanced Accuracy 0.9783 0.9643 1.0000