Multi criteria wrapper improvements to naive bayes learning

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dc.contributor.author Cortizo Pérez, José Carlos
dc.contributor.author Giráldez Betrón, Juan Ignacio
dc.contributor.other Corchado, Emilio
dc.contributor.other Yin, Hujun
dc.contributor.other Botti, Vicente
dc.contributor.other Fyfe, Colin
dc.date.accessioned 2016-07-27T15:46:43Z
dc.date.available 2016-07-27T15:46:43Z
dc.date.issued 2006
dc.identifier.citation Cortizo, J. C., & Giráldez, J. I. (2006). Multi criteria wrapper improvements to naive bayes learning. In E. Corchado, H. Yin, V. Botti & C. Fyfe (Eds.), International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2006) (pp. 419-427). Berlin: Springer. spa
dc.identifier.isbn 9783540454854
dc.identifier.isbn 9783540454878
dc.identifier.issn 03029743
dc.identifier.uri http://hdl.handle.net/11268/5493
dc.description.abstract Feature subset selection using a wrapper means to perform a search for an optimal set of attributes using the Machine Learning Algorithm as a black box. The Naive Bayes Classifier is based on the assumption of independence among the values of the attributes given the class value. Consequently, its effectiveness may decrease when the attributes are interdependent. We present FBL, a wrapper that uses information about dependencies to guide the search for the optimal subset of features and we use the Naive Bayes Classifier as the black-box Machine Learning algorithm. Experimental results show that FBL allows the Naive Bayes Classifier to achieve greater accuracies, and that FBL performs better than other classical filters and wrappers. spa
dc.description.sponsorship SIN FINANCIACIÓN spa
dc.language.iso eng spa
dc.publisher Springer spa
dc.title Multi criteria wrapper improvements to naive bayes learning spa
dc.type conferenceObject spa
dc.description.impact 0.292 SJR (2006) Q2, 79/200 Computer science (miscellaneous); Q4, 77/115 Theoretical computer science spa
dc.identifier.doi 10.1007/11875581_51
dc.rights.accessRights closedAccess en
dc.subject.uem Minería de datos spa
dc.subject.unesco Informática spa
dc.description.filiation UEM spa
dc.peerreviewed Si spa

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