Abstract
Classification is the operation of determining class of the data by forming a model that makes use of data whose categories are previously determined. Data mining techniques are frequently used to form a classifier that determines belonging class of a new data among the predetermined classes. This paper intends to provide comparative analysis of the rule based classifiers for vote pattern analysis. Analyzing the performance of rule based classifiers algorithms namely Decision Table, JRip, OneR, PART and Ridor. The goal of this paper is to specify the best technique from the rules classification technique under the vote dataset and also provide a comparison result each classifier.
Keywords
Rule based classifier, Decision Table, JRip, OneR, PART, Ridor
Citations
IRE Journals:
Aung Nway Oo , Thin Naing
"Rule Based Classifiers For Vote Pattern Analysis" Iconic Research And Engineering Journals Volume 2 Issue 11 2019 Page 295-299
IEEE:
Aung Nway Oo , Thin Naing
"Rule Based Classifiers For Vote Pattern Analysis" Iconic Research And Engineering Journals, 2(11)
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