inparticular,we
focus on the well-known one-vs-one and one-vs-all decomposition strategies,paying special attention
to the final step of the ensembles,the combination of the outputs of the binary classifiers.
Our aim is to develop an empirical analysis of different aggregations to combine these outputs.To do so,we develop
a double study: first,we use different base classifiers in order to observe the suitability and potential of
each combination with in eachclassifier. Then,we compare the performance of these ensemble
techniques with the classifiers’themselves. Hence,we also analyse the improvement with respect to
the classifiers that handle multiple classes in herently.