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

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Published Paper ID:
JETIRDC06039


Registration ID:
221849

Page Number

220-223

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Title

IMPLEMENTATION OF MACHINE LEARNING IN AIR LINE DATA

Abstract

The main objective of the paper is to implement classification and clustering algorithm such as Naive Bayes, K-Means, and Farthest First clustering algorithm using Weka to analyse airline dataset. In addition to that, performance analysis of these algorithms shows that Farthest First outperforms the other algorithms. Data set has been obtained from UCI machine learning repository. The algorithms has been discussed with the results obtained from the tool. The confusion matrix for classification algorithm and the cluster instances for clustering algorithm is also shown in the result.

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"IMPLEMENTATION OF MACHINE LEARNING IN AIR LINE DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.220-223, June 2019, Available :http://www.jetir.org/papers/JETIRDC06039.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

"IMPLEMENTATION OF MACHINE LEARNING IN AIR LINE DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp220-223, June 2019, Available at : http://www.jetir.org/papers/JETIRDC06039.pdf

Publication Details

Published Paper ID: JETIRDC06039
Registration ID: 221849
Published In: Volume 6 | Issue 6 | Year June-2019
DOI (Digital Object Identifier):
Page No: 220-223
Country: Chennai, Tamil Nadu, India .
Area: Engineering
ISSN Number: 2349-5162


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