Multi-label classification search space in the MEKA software
de Sá, Alex G. C., Freitas, Alex A., Pappa, Gisele L.
–arXiv.org Artificial Intelligence
This technical report describes the multi-label classification (MLC) search space in the MEKA software, including the traditional/meta MLC algorithms, and the traditional/meta/pre-processing single-label classification (SLC) algorithms. The SLC search space is also studied because is part of MLC search space as several methods use problem transformation methods to create a solution (i.e., a classifier) for a MLC problem. This was done in order to understand better the MLC algorithms. Finally, we propose a grammar that formally expresses this understatement.
arXiv.org Artificial Intelligence
Nov-27-2018
- Country:
- North America > United States (0.67)
- Genre:
- Research Report (0.51)
- Technology:
- Information Technology > Artificial Intelligence
- Cognitive Science > Problem Solving (1.00)
- Representation & Reasoning
- Uncertainty > Bayesian Inference (1.00)
- Search (1.00)
- Machine Learning
- Statistical Learning (1.00)
- Neural Networks > Perceptrons (0.68)
- Learning Graphical Models > Directed Networks
- Bayesian Learning (1.00)
- Information Technology > Artificial Intelligence