Automated Prediction of Behaviours and Trends in Data Mining
B.Raju1, Rajitha Bonagiri2
1B.Raju*, Assistant Professor, Department of CSE, Kakatiya Institute of Technology & Science, India.
2Rajitha Bonagiri, Assistant Professor, Department of CSE, Vaagdevi College of Engineering, India.
Manuscript received on November 17, 2019. | Revised Manuscript received on 25 November, 2019. | Manuscript published on December 10, 2019. | PP: 8188-5190 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7056129219/2019©BEIESP | DOI: 10.35940/ijitee.B7056.129219
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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: Data mining is the process of discovering likely useful, appealing, as well as previously not known patterns coming from an extensive compilation of data. Data mining is a multidisciplinary field, enticing projects coming from places consisting of data financial institution advancement, expert system, stats, style understanding, information retrieval, semantic networks, knowledge-based units, expert system, high-performance processing, as well as files visual images. This paper delivers a quick concerning architecture, benefits and automated prediction of trends as well as behaviors in Data Mining.
Keywords: Data Mining, Prediction, Architecture
Scope of the Article: Data mining