Rough Sets Base Associative Classification Rules Extraction from Big Data
Hanumanthu Bhukya1, M.Sadanandam2
1Hanumanthu Bhukya*, Full-Time Research Scholar, Department of CSE, UCE & T, Kakatiya University, Warangal, India.
2Dr. M. Sadanandam, Department of CSE, Kakatiya University, Warangal, India.
Manuscript received on October 22, 2019. | Revised Manuscript received on 30 October, 2019. | Manuscript published on November 10, 2019. | PP: 3096-3102 | Volume-9 Issue-1, November 2019. | Retrieval Number: A9140119119/2019©BEIESP | DOI: 10.35940/ijitee.A9140.119119
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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: Big Data is a current burning challenge for the data analytics research community. Many conventional data analytics techniques have been extended to the MapReduce framework to process Big Data. But in our literature review, we find that for the MapReduce system there is an absolute lack of rough set based technique. To facilitate this and recognize the importance of the rule-based classification techniques, we suggest a rough set associative classification rules extraction process for the MapReduce framework. The implementation and evaluation of the Big Data Standard data set demonstrated the efficiency of our suggested approach
Keywords: Classification, Big Data, Current Burning
Scope of the Article: Classification