UGC Approved Journal no 63975

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

Volume 6 Issue 6
June-2019
eISSN: 2349-5162

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

7.95 impact factor calculated by Google scholar

Unique Identifier

Published Paper ID:
JETIRDC06033


Registration ID:
221833

Page Number

189-192

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Title

Population Prediction Using Machine learning

Abstract

The main objective of the paper is to find the best machine learning algorithm to predict the population outcome in the future. This paper discusses about the three algorithms, which are naïve Bayes, IBk and Random Trees. Machine learning tool used for running these algorithms is WEKA. In this test, WEKA is used to analyze the data and the three algorithms are added from the library. The data set is obtained from UCI repository and from number of instances available in the dataset, only limited number of instances is used to run the algorithm to keep the controlled environment for this test. Of all the three algorithms Naïve bayes algorithm shows the highest result.

Key Words

Machine learning, Naïve Bayes, Weka, Lazy IBk, Random trees, UCI repository

Cite This Article

"Population Prediction Using Machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.189-192, June 2019, Available :http://www.jetir.org/papers/JETIRDC06033.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

"Population Prediction Using Machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp189-192, June 2019, Available at : http://www.jetir.org/papers/JETIRDC06033.pdf

Publication Details

Published Paper ID: JETIRDC06033
Registration ID: 221833
Published In: Volume 6 | Issue 6 | Year June-2019
DOI (Digital Object Identifier):
Page No: 189-192
Country: Chennai, Tamil Nadu, India .
Area: Engineering
ISSN Number: 2349-5162


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