Labelled network motifs reveal stylistic subtleties in written texts
Table 4: Accuracy rate (%) in discriminating the debates from the Canadian Hansard into two classes (Original and Translated). The highest accuracies were obtained with the strategy based on labelled motifs.
['[BOLD] Language', '[BOLD] Features', '| [ITALIC] W|', '[BOLD] J48', '[BOLD] kNN', '[BOLD] SVM', '[BOLD] Bayes']
The accuracies are relatively high for such a simple feature set. The results suggest that labelled motifs are extracting information about French to English (and vice-versa) translation and these features lead to accuracies higher than the ones obtained with only the frequency of the most frequent words.