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An Experimental Study of Classification Algorithms Training Performance

Aboalayon, Khald Ali I. (2005) An Experimental Study of Classification Algorithms Training Performance. Masters thesis, Universiti Utara Malaysia.

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Abstract

This thesis evaluates the training performance of classifiers in terms of Root Mean Square Error (RMSE), Training Time and Complexity. The study was based on different data set that were obtained from UCI machine learning database and tested by the WEKA software machine learning tools. The aim of this study is to experiment several classifiers with different data sets to find out the best classifier for a certain data set like nominal, numerical and both, according to the objective of this research.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Data Mining Techniques, Classification, Classification Algorithms
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines
Divisions: Faculty and School System > Faculty of Information Technology
Depositing User: Mrs Shamsiah Mohd Shariff
Date Deposited: 02 Feb 2010 03:58
Last Modified: 24 Jul 2013 12:11
URI: http://etd.uum.edu.my/id/eprint/1250

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