Title: Hierarchical multi-classification with predictive clustering trees in functional genomics
Authors: Struyf, Jan ×
D┼żeroski, Sašo
Blockeel, Hendrik
Clare, Amanda #
Issue Date: 2005
Publisher: Springer
Series Title: Lecture Notes in Computer Science vol:3808 pages:272-283
Conference: Workshop on Computational Methods in Bioinformatics as part of the Twelfth Portuguese Conference on Artificial Intelligence location:Covilha, Portugal date:December 5-8, 2005
Abstract: This paper investigates how predictive clustering trees can be used to predict gene function in the genome of the yeast Saccharomyces cerevisiae. We consider the MIPS FunCat classification scheme, in which each gene is annotated with one or more classes selected from a given functional class hierarchy. This setting presents two important challenges to machine learning: (1) each instance is labeled with a set of classes instead of just one class, and (2) the classes are structured in a hierarchy; ideally the learning algorithm should also take this hierarchical information into account. Predictive clustering trees generalize decision trees and can be applied to a wide range of prediction tasks by plugging in a suitable distance metric. We define an appropriate distance metric for hierarchical multi-classification and present experiments evaluating this approach on a number of data sets that are available for yeast.
ISBN: 978-3-540-30737-2
ISSN: 0302-9743
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Informatics Section
× corresponding author
# (joint) last author

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