Show simple item record Clare, Amanda Džeroski, Sašo Struyf, Jan Blockeel, Hendrik 2006-04-25T08:59:26Z 2006-04-25T08:59:26Z 2005
dc.identifier.citation Clare , A , Džeroski , S , Struyf , J & Blockeel , H 2005 , ' Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics ' . en
dc.identifier.other PURE: 68118
dc.identifier.other PURE UUID: ab77444b-02af-44e9-8fa8-739efd6063f6
dc.identifier.other dspace: 2160/131
dc.identifier.other DSpace_20121128.csv: row: 106
dc.identifier.other Scopus: 33744783942
dc.description Struyf, J., Dzeroski, S. Blockeel, H. and Clare, A. (2005) Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics. In proceedings of the EPIA 2005 CMB Workshop en
dc.description.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. en
dc.language.iso eng
dc.rights en
dc.title Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics en
dc.type /dk/atira/pure/researchoutput/researchoutputtypes/contributiontoconference/paper en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Bioinformatics and Computational Biology Group en
dc.description.status Non peer reviewed en

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