@inproceedings{83e29b55f6b742628e41d781a610cebd,
title = "Measuring diversity and accuracy in ANN ensembles",
abstract = "Performance of classifier ensembles depends on the precision and on the diversity of the members of the ensemble. In this paper we present an experimental study in which the relationship between the accuracy of the ensemble and both the diversity and the accuracy of base learners is analyzed. We conduct experiments on 8 different ANN ensembles and on 5 multiclass data sets. Experimental results show that a high diversity degree among the base learners does not always imply a high accuracy in the ensemble.",
keywords = "Accuracy, ANN, Diversity, Ensemble of classifiers",
author = "Sesmero, {M. Paz} and Alonso-Weber, {Juan Manuel} and Alessandro Giuliani and Giuliano Armano and Araceli Sanchis",
year = "2018",
month = jan,
day = "1",
doi = "10.1007/978-3-030-00374-6_11",
language = "English",
isbn = "9783030003739",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "108--117",
editor = "Antonio Gonzalez and Alicia Troncoso and Francisco Herrera and Sergio Damas and Rosana Montes and Sergio Alonso and Oscar Cordon",
booktitle = "Advances in Artificial Intelligence - 18th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2018, Proceedings",
address = "Germany",
note = "18th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2018 ; Conference date: 23-10-2018 Through 26-10-2018",
}