Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/1190
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dc.contributor.authorTsagalidis, Evangelos-
dc.contributor.authorEvangelidis, Georgios-
dc.date.accessioned2022-08-26T10:58:16Z-
dc.date.available2022-08-26T10:58:16Z-
dc.date.issued2010-
dc.identifier10.1109/PCI.2010.37en_US
dc.identifier.isbn978-1-4244-7838-5en_US
dc.identifier.urihttps://doi.org/10.1109/PCI.2010.37en_US
dc.identifier.urihttps://ruomo.lib.uom.gr/handle/7000/1190-
dc.description.abstractWe use meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Meteorological Station of Mikra (Thessaloniki, Greece) as input to five data mining algorithms with the aim to build classification models for the prediction of the occurrence of precipitation in the station. We focus our study on the effect the selection of the training set has on the performance of the algorithms and more specifically, we attempt to determine the minimum training set size that can ensure effective application of the data mining techniques.en_US
dc.language.isoenen_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectFRASCATI::Natural sciences::Computer and information sciencesen_US
dc.subject.othertraining set sizeen_US
dc.subject.othermeteorological data miningen_US
dc.subject.otherclassificationen_US
dc.titleThe Effect of Training Set Selection in Meteorological Data Miningen_US
dc.typeConference Paperen_US
dc.contributor.departmentΤμήμα Εφαρμοσμένης Πληροφορικήςen_US
local.identifier.volumetitle2010 14th Panhellenic Conference on Informaticsen_US
Appears in Collections:Department of Applied Informatics

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