Pattern Identification for Main Export Products in Sri Lanka through Data Mining

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dc.contributor.authorDarmasena, D.S.P.
dc.contributor.authorSenanayake, S.H.D.
dc.date.accessioned2022-01-04T09:30:17Z
dc.date.available2022-01-04T09:30:17Z
dc.date.issued2016
dc.description.abstractIdentifying the tendencies using data mining techniques is done by this research. Normally, this goes beyond the normal data analysis. This research identifies the effects which can cause to the Sri Lankan Gross Domestic Product (GDP) through many analysing tools. It means the tendencies in export sector of Sri Lankan economy has been examined through this. Export performance is one of the strongest areas of Sri Lanka's economy in the present time. Data mining can be done as predictive analysis through complete and intuitive set of data mining tools. Furthermore, the flexible platform extends prediction into any application. For this purpose, there are lot of learning methods has been followed by Export Development Board and interested parties. But a correct analysis of data has not been done by any of these parties and most of the analysis are done by manually. But in this research the WEKA tool was used to analyse data. So the accuracy will be very high. Different data has been collected through many resources. The information which has been collected is put into logic to create an algorithm. Keywords: Data mining, Classification, Clustering, WEKA, Decision treeen_US
dc.identifier.isbn9789550481095
dc.identifier.urihttp://www.erepo.lib.uwu.ac.lk/bitstream/handle/123456789/8176/236-2016-Pattern%20Identification%20for%20Main%20Export%20Products%20in%20Sri%20Lanka%20through%20Data%20Mining%20%20.pdf?sequence=1&isAllowed=y
dc.language.isoenen_US
dc.publisherUva Wellassa University of Sri Lankaen_US
dc.subjectExporten_US
dc.subjectData Miningen_US
dc.subjectEconomicsen_US
dc.subjectExport Agricultureen_US
dc.subjectFinancial Managementen_US
dc.titlePattern Identification for Main Export Products in Sri Lanka through Data Miningen_US
dc.title.alternativeResearch Symposium 2016en_US
dc.typeOtheren_US
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