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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19456
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
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| Paper Title: | Analysis of Data using PSO model and Random forest |
| Authors Name: | Pranali Tusharrao Sawant , Ragini Pundlik Mahale , Mahesh Chintaman Ahire , Ms. T. S. Pawar |
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IJRTI_180907
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| Published Paper Id: | IJRTI1905052 |
| Published In: | Volume 4 Issue 5, May-2019 |
| DOI: | |
| 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. |
| Keywords: | PSO, Random forest, CCV, feature selection. |
| Cite Article: | "Analysis of Data using PSO model and Random forest", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.4, Issue 5, page no.225 - 227, May-2019, Available :http://www.ijrti.org/papers/IJRTI1905052.pdf |
| Downloads: | 000205102 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI1905052
Registration ID:180907
Published In: Volume 4 Issue 5, May-2019
DOI (Digital Object Identifier):
Page No: 225 - 227 Country: Nashik, Maharashtra, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI1905052 Published Paper PDF: https://www.ijrti.org/papers/IJRTI1905052 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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