A Hybrid Architecture for Multi-Party Conversational Systems
Table 15: Evaluation of different classifiers in the first version of the training set
['[EMPTY]', '[BOLD] Precision', '[BOLD] Recall', '[BOLD] F1', '[BOLD] Accuracy']
Roughly speaking, the 1NN classifier has been able to achieve a level of accuracy that is higher than other well-known classifiers, such as Logistic Regression and Naïve Bayes, showing that 1NN is suitable as a development classifier. Nevertheless, a SVM can perform considerable better than 1NN, reaching accuracies of about 12 percentage points higher, which demonstrates that this type of base classifier is a better choice to be deployed once the system is stable enough. It is worth mentioning that these results consider the leave-one-out validation procedure, given the very low number of samples in some classes.