Dataset 3 (SIH vs. MIH) prediction results from classifiers trained using machine learning methods.

Accuracy, F-measure (F1 Score), precision, recall, correlation coefficient (C.C.), and area under the receiver operating characteristic curve (AUC) of classification for the multi-interface versus singlish-interface dataset are presented. Accuracy and F-measure are reported in percentage. For each machine learning approach, values of k ranged from 1 to 4. Only the classifier with the best performing k-value (as defined by highest correlation coefficient) is shown. Our methods were estimated by cross-validation. The highest performing value(s) for each performance measure is highlighted in bold.