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:
JETIRDC06029


Registration ID:
221829

Page Number

166-171

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Title

FOREST FIRE PREDICTION WITH MACHINE LEARNING

Abstract

Data mining brings understandings, outlines, and descriptive and predictive representations from the large amounts of data available today in many organizations. We have many tools for data mining. One of those tools is rattle which runs on R programming language. In this paper, we used rattle to analyze forest fires which occurred in different regions during different periods of time. We can study whether rattle is an efficient tool by analyzing its time taken for delivering the result, error rate and much more.

Key Words

Data mining, machine learning, rattle, decision tree, error matrix

Cite This Article

"FOREST FIRE PREDICTION WITH MACHINE LEARNING ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.166-171, June 2019, Available :http://www.jetir.org/papers/JETIRDC06029.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

"FOREST FIRE PREDICTION WITH 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. pp166-171, June 2019, Available at : http://www.jetir.org/papers/JETIRDC06029.pdf

Publication Details

Published Paper ID: JETIRDC06029
Registration ID: 221829
Published In: Volume 6 | Issue 6 | Year June-2019
DOI (Digital Object Identifier):
Page No: 166-171
Country: Chennai, Tamil Nadu, India .
Area: Engineering
ISSN Number: 2349-5162


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