UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 5 Issue 5
May-2018
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR1805818


Registration ID:
182664

Page Number

459-466

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Title

Stacked Ensemble Model in Predicting Stock Trend of Three Major Capitalization Companies of NSE

Abstract

Predicting the stock trend movement is an enticing prospect to data scientists. Several Classification algorithms such as Decision tree, Naïve Bayesian, Neural network, k Nearest Neighbor and Support Vector machines are being used in predicting the stock trend. In this study, we presented ensemble based method that pick an optimal combination of multiple predictive models using a stack based ensemble method. Experimental study shows that accuracy of stacked ensemble model is performed better than individual predictive models.

Key Words

stacking, ensemble methods, stock trend, bagging, boosting

Cite This Article

"Stacked Ensemble Model in Predicting Stock Trend of Three Major Capitalization Companies of NSE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 5, page no.459-466, MAY-2018, Available :http://www.jetir.org/papers/JETIR1805818.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Stacked Ensemble Model in Predicting Stock Trend of Three Major Capitalization Companies of NSE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 5, page no. pp459-466, MAY-2018, Available at : http://www.jetir.org/papers/JETIR1805818.pdf

Publication Details

Published Paper ID: JETIR1805818
Registration ID: 182664
Published In: Volume 5 | Issue 5 | Year May-2018
DOI (Digital Object Identifier): http://doi.one/10.1729/IJCRT.17739
Page No: 459-466
Country: Madurai, Tamilnadu, India .
Area: Science & Technology
ISSN Number: 2349-5162
Publisher: IJ Publication


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