UGC Approved Journal no 63975(19)

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

Volume 6 Issue 4
April-2019
eISSN: 2349-5162

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

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Published Paper ID:
JETIRBI06007


Registration ID:
208214

Page Number

37-40

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Title

A Novel Approach on Various Machine Learning Algorithms for Predicting Ground Water Quality

Abstract

Data mining is the process of extracting useful or hidden information from a large database. Extracted information can be used to discover relationships among features, where data objects are grouped according to logical relationships; or to predict unseen objects to one of the predefined groups. In this paper, we aim to investigate four well-known data mining algorithms in order to predict groundwater quality. These algorithms are C5.0 Algorithm, Random Forest, K-Nearest Neighbour (KNN), The experimental results indicate that the C5.0 algorithm outperformed other algorithms in terms of classification accuracy. This work is to build a quality water for people usage and as well as for drinking purposes using data mining techniques such classification and clustering to find suitable data models with high accuracy.

Key Words

Water Quality, C5.0, K-Nearest Neighbour and Random Forest

Cite This Article

"A Novel Approach on Various Machine Learning Algorithms for Predicting Ground Water Quality", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.37-40, April-2019, Available :http://www.jetir.org/papers/JETIRBI06007.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

"A Novel Approach on Various Machine Learning Algorithms for Predicting Ground Water Quality", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp37-40, April-2019, Available at : http://www.jetir.org/papers/JETIRBI06007.pdf

Publication Details

Published Paper ID: JETIRBI06007
Registration ID: 208214
Published In: Volume 6 | Issue 4 | Year April-2019
DOI (Digital Object Identifier):
Page No: 37-40
Country: -, -, -- .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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