UGC Approved Journal no 63975(19)

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

Volume 8 Issue 4
April-2021
eISSN: 2349-5162

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

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Published Paper ID:
JETIRER06035


Registration ID:
308597

Page Number

142-146

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Title

ANALYSING THE STRATEGY USING MACHINE LEARNING ALGORITHM

Abstract

The main object is to find the strategy to win the current trend election by using Machine Learning Algorithm . Machine Learning is the study of computers algorithm that improves automatically through experience and by use of data. It is seen as a part of AI(Artificial Intelligence). Machine Learning Algorithm are the programs that adjust themselves to perform better as they are exposed to more data given by the user. There are many strategy used by various parties, using Machine Learning Algorithm is used to analyze the best strategy that can help the party to win the election.

Key Words

Machine Learning Algorithm, Strategy.

Cite This Article

"ANALYSING THE STRATEGY USING MACHINE LEARNING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.142-146, April-2021, Available :http://www.jetir.org/papers/JETIRER06035.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

"ANALYSING THE STRATEGY USING MACHINE LEARNING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp142-146, April-2021, Available at : http://www.jetir.org/papers/JETIRER06035.pdf

Publication Details

Published Paper ID: JETIRER06035
Registration ID: 308597
Published In: Volume 8 | Issue 4 | Year April-2021
DOI (Digital Object Identifier):
Page No: 142-146
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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