CLASSIFICATION OF DIFFERENT FOREST TYPES W ITH MACHINE LEARNING ALGORITHMS

dc.contributor.authorSabanci, Kadir
dc.contributor.authorUnlersen, M. Fahri
dc.contributor.authorPolat, Kemal
dc.date.accessioned2024-02-23T14:45:03Z
dc.date.available2024-02-23T14:45:03Z
dc.date.issued2016
dc.departmentNEÜen_US
dc.description22nd Annual International Scientific Conference on Research for Rural Development -- MAY 18-20, 2016 -- Latvia Univ Agr, Jelgava, LATVIAen_US
dc.description.abstractIn this study, forest type mapping data set taken from UCI (University of California, Irvine) machine learning repository database has been classified using different machine learning algorithms including Multilayer Perceptron, k-NN, J48, Naive Bayes, Bayes Net and KStar. In this dataset, there are 27 spectral values showing the type of three different forests (Sugi, Hinoki, mixed broadleaf). As the performance measure criteria, the classification accuracy has been used to evaluate the classifier algorithms and then to select the best method. The best classification rates have been obtained 90.43% with MLP, and 89.1013% with k-NN classifier (for k=5). As can be seen from the obtained results, the machine learning algorithms including MLP and k-NN classifier have obtained very promising results in the classification of forest type with 27 spectral features.en_US
dc.identifier.endpage260en_US
dc.identifier.issn1691-4031
dc.identifier.startpage254en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12452/17235
dc.identifier.wosWOS:000391253000041en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherLatvia Univ Life Sciences & Technologiesen_US
dc.relation.ispartofResearch For Rural Development 2016, Vol. 1en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectForest Typesen_US
dc.subjectMultilayer Perceptronen_US
dc.subjectK-Nn Classifieren_US
dc.subjectData Miningen_US
dc.titleCLASSIFICATION OF DIFFERENT FOREST TYPES W ITH MACHINE LEARNING ALGORITHMSen_US
dc.typeConference Objecten_US

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