- author = "Jose M. Moyano and Eva L. Gibaja and Krzysztof J. Cios and Sebastian Ventura",
- title = "Tree-Shaped Ensemble of Multi-Label Classifiers using Grammar-Guided Genetic Programming",
- booktitle = "2020 IEEE Congress on Evolutionary Computation, CEC 2020",
- year = "2020",
- editor = "Yaochu Jin",
- pages = "paper id24049",
- address = "internet",
- month = "19-24 " # jul,
- organization = "IEEE Computational Intelligence Society",
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming, Multi-label classification, Ensemble learning",
- isbn13 = "978-1-7281-6929-3",
-
DOI = "
doi:10.1109/CEC48606.2020.9185661",
- size = "8 pages",
- abstract = "Multi-label classification paradigm has had a growing interest because of the emergence of a large number of classification problems where each of the instances of the data can be associated with several output labels simultaneously. Several ensemble methods were proposed to solve the multilabel classification problem. However, most of them simply create diversity in the ensemble by following a random procedure and give the same importance to all members. In this paper, we propose a Grammar-Guided Genetic Programming algorithm to build ensembles of multi-label classifiers. Given a pool of multilabel classifiers, each of them modeling dependencies among a subset of k labels, they are combined into a tree-shaped ensemble. At each node of the tree, predictions of its children nodes are combined, while each leaf represents a classifier from the pool. We propose two configurations for the method: using a fixed value of k for all classifiers in the pool, or using a variable value of k for each classifier, thus being able to capture relationships among groups of labels of different size in the ensemble. The experiments performed over sixteen multi-label dataset and using five evaluation metrics demonstrated that our method performs significantly better than the state-of-the-art ensembles of multilabel classifiers.",
-
notes = "G3P-kEMLC, pop=50, 150 gens, crossover & mutation, max
tree size. compare with RAkEL. Holm's stats test. k=6
to k=174
https://wcci2020.org/
University of Cordoba, Spain; Virginia Commonwealth University, United States of America.
Also known as \cite{9185661}",
