An Efficient System to Predict and Analyze Stock Data u sing Hadoop Techniques
Jithina Jose1, Suja Cherukullapurath Mana2, B Keerthi Samhitha3
1Jithina Jose, Assistant Professor, School of Computing, Sathyabama Institute of Science and Technology, Chennai, India.
2Suja Cherukullapurath Mana, Assistant Professor, School of Computing, Sathyabama Institute of Science and Technology, Chennai, India.
3B Keerthi Samhitha, Assistant Professor, School of Computing, Sathyabama Institute of science and Technology, Chennai, India.
Manuscript received on 01 March 2019 | Revised Manuscript received on 04 March 2019 | Manuscript published on 30 July 2019 | PP: 1039-1043 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1824078219/19©BEIESP | DOI: 10.35940/ijrte.B1824.078219
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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: Stocks, they assume significant job in keeping up the capital inflow of an organization or to keep up the business of the nation. As indicated by certain reports, 1.46 billion exchanges are done every day in NYSE. Increment of open enthusiasm on the promoting came about to expand the stock exchanges flawlessly. Because of the expansion of number of exchanges one can abuse the information and the examples which exists in the information by applying present day strategies like HDFS(Hadoop Distributed File System) .Taking the upside of size of the information and by allocating information to dispersed frameworks one can accomplish the plots from the information and when this procedure is done powerfully it can give an estimation of future examples.
Index Terms: Stock Prediction, Linear Regression, Logistic Regression, Genetic Algorithm.
Scope of the Article: Energy Efficient Building Technology