For large-scale classification problems, the training samples can be clustered beforehand as a downsampling pre-process, and then only the obtained clusters are used for training....
Usually, performance of classifiers is evaluated on real-world problems that mainly belong to public repositories. However, we ignore the inherent properties of these data and how...
Background: The main goal of the PROMISE repository is to enable reproducible, and thus verifiable or refutable research. Over time, plenty of data sets became available, especial...
A common way to model multiclass classification problems is by means of Error-Correcting Output Codes (ECOCs). Given a multiclass problem, the ECOC technique designs a code word fo...
Sergio Escalera, David M. J. Tax, Oriol Pujol, Pet...
Abstract. We propose inductive distance-based methods for instance classification and retrieval in ontologies. Casting retrieval as a classification problem with the goal of assess...