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Implementation of Classification System for Dry Zone Plantation Based on ID3 Algorithm

http://hdl.handle.net/20.500.12678/0000004161
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26353073-8e8d-4283-bfcb-ecfb79cf7a32
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55305.pdf 55305.pdf (298 Kb)
Publication type
Article
Upload type
Publication
Title
Title Implementation of Classification System for Dry Zone Plantation Based on ID3 Algorithm
Language en
Publication date 2009-12-30
Authors
Hlaing, Thazin
Description
Classification is data analysis process that can be used to extract models describing important data classes or predict future data. Classification of large data sets is an important data mining problem. Decision tree, mainly used for classification purpose, is a classifier method in the form of a tree structure. Decision tree algorithms are a method for approximating discrete-valued target functions, in which the learned function is represented by a decision tree. The data set of plantation system for Dry Zone is used to provide the aim of the system. The aim of this paper is to present how to construct decision trees (ID3), show its rules and evaluate the performance of model and to test the unknown data set. An accuracy method, hold-out, is allowed to use in this system for the validity of rules.
Keywords
ID3, Classification, Data mining, Accuracy
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/1859
Journal articles
Fourth Local Conference on Parallel and Soft Computing
Conference papers
Books/reports/chapters
Thesis/dissertations
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