269 citations · 460 across the 8 of their papers we have counts for
3 papers · 1 filter
A snapshot on nonstandard supervised learning problems: taxonomy, relationships and methods
David Charte, Francisco Charte, Salvador García +1
Machine learning is a field which studies how machines can alter and adapt their behavior, improving their actions according to the information they are given. This field is subdiv…
Tips, guidelines and tools for managing multi-label datasets: the mldr.datasets R package and the Cometa data repository
Francisco Charte, Antonio J. Rivera, David Charte +2
New proposals in the field of multi-label learning algorithms have been growing in number steadily over the last few years. The experimentation associated with each of them always…
A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines
David Charte, Francisco Charte, Salvador García +2
Many of the existing machine learning algorithms, both supervised and unsupervised, depend on the quality of the input characteristics to generate a good model. The amount of these…