A Model for Accurate Prediction of Child Immunization Data for Knowledge Discovery using Bayesian TAN and Naive Bayes Classifiers
Sourabh1, Vibhakar Mansotra2
1Sourabh, Department of Computer Science & IT, University of Jammu.
2Professor Vibhakar Mansotra, Department of Computer Science & IT, University of Jammu.

Manuscript received on November 20, 2019. | Revised Manuscript received on November 26, 2019. | Manuscript published on 30 November, 2019. | PP: 3335-3343 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8118118419/2019©BEIESP | DOI: 10.35940/ijrte.D8118.118419

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Knowledge Discovery in Databases (KDD) is a splendid methodology of discovering knowledge from gigantic databases by using its various stages viz. Data Selection, Data Preprocessing, Data Transformation, Data Mining and Interpretation/Evaluation. Data Mining is a vital sub-process of KDD methodology that is particularly used to apply the various mining algorithms on the data. In the present research paper, the authors have made an attempt to discover new knowledge by classifying the child immunization data of Jammu and Kashmir State of India. The data for the present work was collected from a web portal named as Health Management Information System (HMIS) facilitated by Ministry of Health and Family Welfare (MoHFW), Government of India. The data consists of diverse health parameters pertaining to the immunization of children and for the present study, the child immunization data of all districts of Jammu and Kashmir State was considered. Two classifiers viz. Bayesian TAN and Naïve Bayes were employed for classifying the districts of Jammu and Kashmir State into High IMR and Low IMR districts based on the available past data from 2014 to 2018. Additionally, various measurement methods have been used to evaluate the performance of the models developed by Bayesian TAN and Naïve Bayes.
Keywords: KDD, Data Mining, Classification, Bayesian TAN, Naïve Bayes, Child Immunization.
Scope of the Article: Data Mining.