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dc.date.accessioned 2011-10-27T13:19:40Z
dc.date.available 2011-10-27T03:00:00Z
dc.date.issued 2011-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/9699
dc.description.abstract The classification problem is one of the main issues in data mining because it aims to extract a classifier which can be used to predict the classes of objects whose class table are unknown. This paper deals with classifying the income database with the entropy based method for analyzing the income is high or low. This method incorporates two mathematical techniques Entropy and Information Gain (IG) with Interactive Dichotomize 3 Algorithm (ID3). Subsets are calculated through Entropy. We fix the threshold point based on the fuzzy approach and the factors are identified using IG. The ID3 algorithm is used to derive a decision tree which classifies the income. This method also helps to extract logical rules that could be used in classifying high or low based on income with various attributed. en
dc.format.extent 81-85 es
dc.language en es
dc.subject Clasificación es
dc.subject Entropía es
dc.subject Árboles de Decisión es
dc.title Fuzzy Classification to Classify the Income Category Based On Entropy en
dc.type Articulo es
sedici.identifier.uri http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct11-5.pdf es
sedici.identifier.issn 1666-6038 es
sedici.creator.person Srinivasan, Vaiyapuri es
sedici.creator.person Govind, Rajenderan es
sedici.creator.person Jagannathan, Vandar Kuzhali es
sedici.creator.person Murugesan, Aruna es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc/3.0/
sedici.description.peerReview peer-review es
sedici2003.identifier ARG-UNLP-ART-0000007600 es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 11, no. 2 es


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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)