7 citations · 13 across the 3 of their papers we have counts for
4 papers · 1 filter
An Extensive Experimental Evaluation of Automated Machine Learning Methods for Recommending Classification Algorithms (Extended Version)
Márcio P. Basgalupp, Rodrigo C. Barros, Alex G. C. de Sá +4
This paper presents an experimental comparison among four Automated Machine Learning (AutoML) methods for recommending the best classification algorithm for a given input dataset.…
A Robust Experimental Evaluation of Automated Multi-Label Classification Methods
Alex G. C. de Sá, Cristiano G. Pimenta, Gisele L. Pappa +1
Automated Machine Learning (AutoML) has emerged to deal with the selection and configuration of algorithms for a given learning task. With the progression of AutoML, several effect…
Multi-label classification search space in the MEKA software
Alex G. C. de Sá, Cristiano G. Pimenta, Gisele L. Pappa +1
This supplementary material aims to describe the proposed multi-label classification (MLC) search spaces based on the MEKA and WEKA softwares. First, we overview 26 MLC algorithms…
A New Hierarchical Redundancy Eliminated Tree Augmented Naive Bayes Classifier for Coping with Gene Ontology-based Features
Cen Wan, Alex A. Freitas
The Tree Augmented Naive Bayes classifier is a type of probabilistic graphical model that can represent some feature dependencies. In this work, we propose a Hierarchical Redundanc…