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Rule Based Classifiers For Vote Pattern Analysis
Subject area: Science,Engineering and Technology · Area of research: Computer Engineering
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
References
[1] Aditi Mahajan, Anita Ganpati, “Performance Evaluation of Rule Based Classification Algorithms”, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 3 Issue 10, October 2014.
[2] Vivek kshirsagar, Madhuri S.Joshi, “Rule Based Classifier Models For Intrusion Detection System”, International Journal of Computer Science and Information Technologies, Vol. 7 (1) , 2016, 367-370
[3] Srinivas Murti, Mahantappa, “Using Rule Based Classifiers for the Predictive Analysis of Breast Cancer Recurrence”, Journal of Information Engineering and Applications www.iiste.org ISSN 2224-5782 (print) ISSN 2225-0506 (online) Vol 2, No.2, 2012.
[4] Dr. Vaishali S. Parsania, Dr. N. N. Jani, Navneet H Bhalodiya, “Applying Naïve bayes, BayesNet, PART, JRip and OneR Algorithms on Hypothyroid Database for Comparative Analysis”, INTERNATIONAL JOURNAL OF DARSHAN INSTITUTE ON ENGINEERING RESEARCH & EMERGING TECHNOLOGIES Vol. 3, No. 1, 2014.
[5] Namrata Singh and Pradeep Singh, “Rule Based Approach for prediction of Chronic Kidney Disease: A Comparative Study”, iomedical & Pharmacology Journal Vol. 10(2), 867-874 (2017).
[6] V. Veeralakshmi, “Ripple down Rule learner (RIDOR) Classifier for IRIS Dataset”, International Journal of Computer Science Engineering (IJCSE), May 2015.
[7] Aditi Mahajan, Anita Ganpati,” Performance Evaluation of Rule Based Classification Algorithms”, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 3 Issue 10, October 2014.
[8] Dr. Neeraj Bhargava, Aakanksha Jain, Abhishek Kumar, Dr. Dac-Nhuong Le, ” Detection of Malicious Executables Using Rule Based Classification Algorithms”, Proceedings of the First International Conference on Information Technology and Knowledge Management, 2018.
[9] https://en.wikipedia.org/wiki/Rule- based_machine_learning
[10] Murat Koklu, et al., “APPLICATIONS OF RULE BASED CLASSIFICATION TECHNIQUES FOR THORACIC SURGERY”, Joint International Conference (Technology Innovation and Industrial Management), 2015 May.
[11] Anil RAJPUT, Ramesh Prasad Aharwal, Meghna Dubey, S.P. Saxena, (2011) “J48 and JRIP Rules for E-Governance Data.” IJCSS-448.
[12] Gaya Buddhinath and Damien Derry, “A Simple Enhancement to One Rule Classification.” Department of Computer Science & Software Engineering University of Melbourne, Australia, 2006.
[13] Eibe Frank, Ian H. Witten, “Generating Accurate Rule Sets Without Global Optimization”. In: Fifteenth International Conference on Machine Learning, 144-151, 1998.
[14] Gaines, B.R., Paul Compton, J. 1995. Induction of Ripple-Down Rules Applied to Modeling Large Databases, Intell. Inf. Syst. 5(3):211-228.
How to cite this paper
@article{1701260,
author = {Aung Nway Oo, Thin Naing},
title = {Rule Based Classifiers For Vote Pattern Analysis},
journal = {Iconic Research And Engineering Journals},
year = {2019},
volume = {2},
number = {11},
pages = {295-299},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1701260.pdf},
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},
month = {May},
}