Applying Naïve bayes, BayesNet, Part, JRip and OneR Algorithms on Hypothyroid Database for Comparative Analysis

Parsania, Vaishali S.; Jani, N.N.; Bhalodiya, Navneet H.

dc.contributor.author	Parsania, Vaishali S.
dc.contributor.author	Jani, N.N.
dc.contributor.author	Bhalodiya, Navneet H.
dc.date.accessioned	2021-09-03T10:45:39Z
dc.date.available	2021-09-03T10:45:39Z
dc.date.issued	2014-06-01
dc.identifier.citation	Parsania, Vaishali, Navneet Bhalodiya, and N. N. Jani. "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, 3(1),61-64.	en_US
dc.identifier.uri	http://ijdieret.in/JournalIssues/June-2014-Vol-3-No-1/48/PaperDetail
dc.identifier.uri	http://10.9.150.37:8080/dspace//handle/atmiyauni/745
dc.description.abstract	This research paper intends to provide comparative analysis of Data Mining classification algorithms. Some benchmarking classification algorithms like Naïve Bayes, Bayesian Network, JRip, OneR and PART are selected based on literature survey. These classification algorithms are applied on Hypothyroid health database for the purpose of finding better techniques for classification. The multiple parameters taken into considerations for analytical purpose are accuracy, sensitivity, Precision, False positive Rate and f-measure. Results of all these parameters are taken for all the described classification techniques. At the last the results are provided in tabular form to facilitate comparative analysis for the hypothyroid database	en_US
dc.language.iso	en_US	en_US
dc.publisher	International Journal of Darshan Institute on Engineering Research & Emerging Technologies	en_US
dc.subject	Data Mining, Knowledge Discovery in Databases (KDD), Naïve Bayes, Bayesian Network, JRip, OneR and PART	en_US
dc.title	Applying Naïve bayes, BayesNet, Part, JRip and OneR Algorithms on Hypothyroid Database for Comparative Analysis	en_US
dc.type	Article	en_US