2.4. Training Models This study looked into a variety of machine learning and deep learning models. Table 2 shows the investigated models for the sixteen feature set. The choice of selected models was motivated by the success of these algorithms in supporting fast-prototyping when working with various frame-level or file-level features. Various combinations of classifiers and their hyperparameters were fine tuned for every feature set, and the resulting training losses were compared.
