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Published in:
2010 | OriginalPaper | Chapter
An Experimental Comparison of Hierarchical Bayes and True Path Rule Ensembles for Protein Function Prediction
Authors : Matteo Re, Giorgio Valentini
Published in: Multiple Classifier Systems
Publisher: Springer Berlin Heidelberg
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The computational genome-wide annotation of gene functions requires the prediction of hierarchically structured functional classes and can be formalized as a multiclass, multilabel, multipath hierarchical classification problem, characterized by very unbalanced classes. We recently proposed two hierarchical protein function prediction methods: the Hierarchical Bayes (
hbayes
) and True Path Rule (
tpr
) ensemble methods, both able to reconcile the prediction of component classifiers trained locally at each term of the ontology and to control the overall precision-recall trade-off. In this contribution, we focus on the experimental comparison of the
hbayes
and
tpr
hierarchical gene function prediction methods and their cost-sensitive variants, using the model organism
S. cerevisiae
and the FunCat taxonomy. The results show that cost-sensitive variants of these methods achieve comparable results, and significantly outperform both
flat
and their non cost-sensitive hierarchical counterparts.