ISSN2456-3315
Impact Factor10.57
UGC CAREApproved
Low Cost₹599 / $45
CrossRefDOI
ESTD2016
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
Analysis of Data using PSO model and Random forest
Authors
Pranali Tusharrao Sawant , Ragini Pundlik Mahale , Mahesh Chintaman Ahire , Ms. T. S. Pawar
Keywords
PSO, Random forest, CCV, feature selection.
Abstract
Big data is rising many technical challenges in today's world which affects both academic researches as well as IT sectors. The reason behind this is the streaming data and the data dimensionality. This was found that streaming data accumulates exponentially making traditional Methods to become infeasible during real time data mining. When it comes to mining high dimensional data, the search space from which an optimal feature subset is selected grows exponentially in size, leading to an large demand in computation. So, to solve this problem, a novel lightweight feature selection is proposed. The feature selection is designed particularly for mining streaming data on the fly, by using particle swarm optimization (PSO) type of swarm search that achieves enhanced analytical accuracy within reasonable processing time. In this project, a collection of Big Data with exceptionally large degree of dimensionality are put under test of our new feature selection algorithm for performance evaluation.
Full Paper, Downloads & Preview
How To Cite
Choose the style your journal or department asks for, then copy it. Every version below is generated from this paper's own record.
IJRTI — journal style
"Analysis of Data using PSO model and Random forest", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.4, Issue 5, page no.225 - 227, May-2019, Available :https://ijrti.org/papers/IJRTI1905052.pdf
APA — 7th edition
Sawant, P. T., Mahale, R. P., Ahire, M. C., & Pawar, T. S. (2019). Analysis of Data using PSO model and Random forest. International Journal for Research Trends and Innovation, 4(5), 225 - 227. https://ijrti.org/viewpaperforall.php?paper=IJRTI1905052
MLA — 9th edition
Sawant, Pranali Tusharrao, et al. "Analysis of Data using PSO model and Random forest." International Journal for Research Trends and Innovation, vol. 4, no. 5, 2019, pp. 225 - 227, https://ijrti.org/viewpaperforall.php?paper=IJRTI1905052.
Chicago — 17th, bibliography
Sawant, Pranali Tusharrao, et al. "Analysis of Data using PSO model and Random forest." International Journal for Research Trends and Innovation 4, no. 5 (2019): 225 - 227. https://ijrti.org/viewpaperforall.php?paper=IJRTI1905052.
Harvard — author–date
Sawant, P.T. et al. (2019) 'Analysis of Data using PSO model and Random forest', International Journal for Research Trends and Innovation, 4(5), pp. 225 - 227. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI1905052
IEEE — numbered reference
P. T. Sawant, R. P. Mahale, M. C. Ahire and T. S. Pawar, "Analysis of Data using PSO model and Random forest," IJRTI, vol. 4, no. 5, pp. 225 - 227, May. 2019.
Vancouver — biomedical
Sawant PT, Mahale RP, Ahire MC, Pawar TS. Analysis of Data using PSO model and Random forest. IJRTI. 2019 May;4(5):225 - 227.
AMA — 11th edition
Sawant PT, Mahale RP, Ahire MC, Pawar TS. Analysis of Data using PSO model and Random forest. IJRTI. 2019;4(5):225 - 227. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI1905052
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI1905052,
author = {Pranali Tusharrao Sawant and Ragini Pundlik Mahale and Mahesh Chintaman Ahire and T. S. Pawar},
title = {Analysis of Data using PSO model and Random forest},
journal = {International Journal for Research Trends and Innovation},
volume = {4},
number = {5},
pages = {225 - 227},
year = {2019},
month = {May},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI1905052}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Sawant, Pranali Tusharrao
AU - Mahale, Ragini Pundlik
AU - Ahire, Mahesh Chintaman
AU - Pawar, T. S.
TI - Analysis of Data using PSO model and Random forest
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 4
IS - 5
PY - 2019
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI1905052
SP - 225
EP - 227
ER -
Issue
Volume 4 Issue 5,
May-2019
Pages : 225 - 227
Other Publication Details
Paper Reg. ID
IJRTI_180907
Published Paper ID
IJRTI1905052
Downloads
205,643
Research Area
Engineering
Country
Nashik, Maharashtra, India
Published
May 2019
Published Paper PDF
https://ijrti.org/papers/IJRTI1905052.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI1905052
About Publisher
International Journal for Research Trends and Innovation
Published by IJRTI (JW Publication)
2456-3315
ISSN
10.57
Impact Factor
2016
ESTD Year
Open
Access
Impact Factor 10.57 calculated by Google Scholar and Semantic Scholar.
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 10.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
UGC CARE Approved Journal — Transparent Peer-reviewed journal aligned with UGC’s 2025 suggestive parameters, with CrossRef DOI registration and Scopus Standard metadata on every published paper.
Licence
© 2019 — Authors hold the copyright of this article.
This work is licensed under a
Creative Commons Attribution 4.0 International License
and The Open Definition.
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0),
which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
Disclaimer:
The content, data and findings in this article are based on the authors’ research and have been
peer-reviewed for academic purposes only. Readers are advised to verify all information before practical
or commercial use. The journal and its editorial board are not liable for any errors, losses or
consequences arising from its use.
Declarations
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
