dc.creator | Ruiz, Roberto | es |
dc.creator | Pontes Balanza, Beatriz | es |
dc.creator | Giráldez, Raúl | es |
dc.creator | Aguilar Ruiz, Jesús Salvador | es |
dc.date.accessioned | 2022-03-01T11:00:28Z | |
dc.date.available | 2022-03-01T11:00:28Z | |
dc.date.issued | 2006 | |
dc.identifier.citation | Ruiz, R., Pontes Balanza, B., Giráldez, R. y Aguilar Ruiz, J.S. (2006). Gene Ranking from Microarray Data for Cancer Classification : A Machine Learning Approach. En KES 2006: 10th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (1272-1280), Bournemouth, UK: Springer. | |
dc.identifier.isbn | 978-3-540-46537-9 | es |
dc.identifier.issn | 0302-9743 | es |
dc.identifier.uri | https://hdl.handle.net/11441/130281 | |
dc.description.abstract | Traditional gene selection methods often select the
top–ranked genes according to their individual discriminative power. We
propose to apply feature evaluation measure broadly used in the machine
learning field and not so popular in the DNA microarray field. Besides,
the application of sequential gene subset selection approaches is included.
In our study, we propose some well-known criteria (filters and wrappers)
to rank attributes, and a greedy search procedure combined with three
subset evaluation measures. Two completely different machine learning
classifiers are applied to perform the class prediction. The comparison is
performed on two well–known DNA microarray data sets. We notice that
most of the top-ranked genes appear in the list of relevant–informative
genes detected by previous studies over these data sets. | es |
dc.description.sponsorship | Comisión Interministerial de Ciencia y Tecnología (CICYT) TIN2004–00159 | es |
dc.description.sponsorship | Comisión Interministerial de Ciencia y Tecnología (CICYT) TIN2004-06689C0303 | es |
dc.format | application/pdf | es |
dc.format.extent | 9 | es |
dc.language.iso | eng | es |
dc.publisher | Springer | es |
dc.relation.ispartof | KES 2006: 10th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (2006), pp. 1272-1280. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | Gene Ranking from Microarray Data for Cancer Classification : A Machine Learning Approach | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.projectID | TIN2004–00159 | es |
dc.relation.projectID | TIN2004-06689C0303 | es |
dc.relation.publisherversion | https://link.springer.com/chapter/10.1007/11893004_161 | es |
dc.identifier.doi | 10.1007/11893004_161 | es |
dc.publication.initialPage | 1272 | es |
dc.publication.endPage | 1280 | es |
dc.eventtitle | KES 2006: 10th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems | es |
dc.eventinstitution | Bournemouth, UK | es |
dc.relation.publicationplace | Berlin, Germany | es |
dc.identifier.sisius | 6533880 | es |
dc.contributor.funder | Comisión Interministerial de Ciencia y Tecnología (CICYT). España | es |