Classification tree generation constrained with variable weights

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract


Trees are a useful framework for classifying entities whose attributes are, at least partially, related through a common ancestry, such as species of organisms, family members or languages. In some common applications, such as phylogenetic trees based on DNA sequences, relatedness can be inferred from the statistical analysis of unweighted attributes.
In this paper we present a Constraint Programming approach that can enforce consistency
between bounds on the relative weight of each trait and tree topologies, so that the user ...
Original languageUnknown
Title of host publicationLecture notes in computer science
Pages274-283
ISBN (Electronic)978-3-642-21344-1
DOIs
Publication statusPublished - 1 Jan 2011
Event4th international conference on Interplay between natural and artificial computation -
Duration: 1 Jan 2011 → …

Conference

Conference4th international conference on Interplay between natural and artificial computation
Period1/01/11 → …

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