Classification of Metabric Clinical Dataset using Naive Bayes Classifier
E. Jenifer Sweetlin1, D. Narain Ponraj2
1E. Jenifer Sweetlin, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Tirunelveli, India.
2D. Narain Ponraje, Department of ECE, Karunya Institute of Technology and Sciences, Coimbatore, India.
Manuscript received on September 12, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 4834-4837 | Volume-8 Issue-12, October 2019. | Retrieval Number: L37031081219/2019©BEIESP | DOI: 10.35940/ijitee.L3703.1081219
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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: The rapid growth of the internet and its applications makes data grow to huge volumes. The Relational Database Management Systems are inefficient to handle huge volumes of data and so nowadays, Big Data technology is being used by many organizations such as Facebook, Twitter etc. Big Data technology is very useful for organizations to take proper decisions to attain their goals and in mounting themselves organization to full fledge. The use of this technology is broadly widened across all fields of Science, Medicine, Technology, and Business, so it is mandatory to acquire knowledge about Big Data concepts. Thus, acquiring knowledge on the technological revolution from traditional Database Management System to Big Data is significant. In this paper, we have discussed about big data and its evolution, characteristics, data sources, formats, Stages of Big Data process. A huge volume of clinical dataset has been considered and it is analyzed using Naive Bayes Classifier.
Keywords: Metabric Dataset, Big Data, Naive Bayes
Scope of the Article: Big Data Analytics