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Classification tree generation constrained with variable weights
2011
BEDJK11
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 can best determine which sets of traits to use and how the entities are likely to be related.
In proceedings
Pedro Barahona, Gemma Bel Enguix, Verónica Dahl, Maria Dolores Jimenez-Lopez, Ludwig Krippahl
Proceedings of the 4th international conference on Interplay between natural and artificial computation
Lecture Notes in Computer Science
Springer
Berlin-Heidelberg
6686
274-283
978-3-642-21343-4
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Pedro Barahona and Gemma Bel Enguix and Verónica Dahl and Maria Dolores Jimenez-Lopez and Ludwig Krippahl, Classification tree generation constrained with variable weights, , Proceedings of the 4th international conference on Interplay between natural and artificial computation, Lecture Notes in Computer Science, Springer, Berlin-Heidelberg, Vol. 6686, ISBN 978-3-642-21343-4, Pag. 274-283, 2011.
<a href="/people/members/view.php?code=7e27bc13fad97e99cd21ea6914d55659" class="author">Pedro Barahona</a>, Gemma Bel Enguix, Verónica Dahl, Maria Dolores Jimenez-Lopez and <a href="/people/members/view.php?code=195d68ea5904b58472fd8c8aedcae233" class="author">Ludwig Krippahl</a>, <b>Classification tree generation constrained with variable weights</b>, <u>Proceedings of the 4th international conference on Interplay between natural and artificial computation</u>, Lecture Notes in Computer Science, <a href="http://www.springer.com" title="Link to external entity..." target="_blank" class="publisher">Springer</a>, Berlin-Heidelberg, Vol. 6686, ISBN 978-3-642-21343-4, Pag. 274-283, 2011.
@inproceedings {BEDJK11, author = {Pedro Barahona and Gemma Bel Enguix and Ver{\'o}nica Dahl and Maria Dolores Jimenez-Lopez and Ludwig Krippahl}, title = {Classification tree generation constrained with variable weights}, booktitle = {Proceedings of the 4th international conference on Interplay between natural and artificial computation}, series = {Lecture Notes in Computer Science}, publisher = {Springer}, address = {Berlin-Heidelberg}, volume = {6686}, pages = {274-283}, isbn = {978-3-642-21343-4}, 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 can best determine which sets of traits to use and how the entities are likely to be related.}, year = {2011}, }
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