@inproceedings{6413a2777c064cb3a221014904fb1c54,
title = "Hypothesis diversity in ensemble classification",
abstract = "The paper discusses the issue of hypothesis diversity in ensemble classifiers. The measures of diversity previously proposed in the literature are analyzed inside a unifying framework based on Monte Carlo stochastic algorithms. The paper shows that no measure is useful to predict ensemble performance, because all of them have only a very loose relation with the expected accuracy of the classifier.",
author = "Lorenza Saitta",
year = "2006",
doi = "10.1007/11875604_73",
language = "English",
isbn = "354045764X",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "662--670",
booktitle = "Foundations of Intelligent Systems - 16th International Symposium, ISMIS 2006, Proceedings",
address = "Germany",
note = "16th International Symposium on Methodologies for Intelligent Systems, ISMIS 2006 ; Conference date: 27-09-2006 Through 29-09-2006",
}