Výsledky vyhledávání - "R. M. Chandrasekaran"

A taxonomy on impact of label noise and feature noise using machine learning techniques

Autor: A. Shanthini, P. Supraja, G. Vinodhini, R. M. Chandrasekaran

Publikováno v: Soft Computing. 23:8597-8607

Soft computing techniques are effective techniques that are used in prediction of noise in the dataset which causes misclassification. In classification, it is expected to have perfect labeling, but the noise present in data has impact on the label m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::96932316b06b8c4aba50ae56bee6b2fc
https://doi.org/10.1007/s00500-019-03968-7

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A Dummy Packet-Based Hybrid Security Framework for Mitigating Routing Misbehavior in Multi-Hop Wireless Networks

Autor: T. Sakthivel, R. M. Chandrasekaran

Publikováno v: Wireless Personal Communications. 101:1581-1618

Wireless networks have emerged as a key enabling technology, expanding rapidly and offers numerous potential applications. The security issues have to be adequately addressed to realize the potential of multi-hop cooperative wireless network scenario

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::38c99cb8935fb26d9652f22d98c6c5db
https://doi.org/10.1007/s11277-018-5778-2

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Predicting Students’ Academic Performance in the University Using Meta Decision Tree Classifiers

Autor: G. Vinodhini, R. M. Chandrasekaran, A. Shanthini

Publikováno v: Journal of Computer Science. 14:654-662

Student performance prediction is an area of concern for educational institutions. At the University level learning system, the method or rule adopted to identify the candidates who pass or fail differs depending on various factors such as the course

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d6e302ceae30aa7c41c64888ea63a107
https://doi.org/10.3844/jcssp.2018.654.662

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A sampling based sentiment mining approach for e-commerce applications

Autor: R. M. Chandrasekaran, G. Vinodhini

Publikováno v: Information Processing & Management. 53:223-236

We propose 3 vector models by varying the feature size.We propose an integrative approach for imbalanced datasets.We analyze the effect of imbalance ratio in sentiment learning.Proposed method performs more accurately than baseline models. Emerging t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f16f663089743bddfd77458ef57f5766
https://doi.org/10.1016/j.ipm.2016.08.003

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A comparative performance evaluation of neural network based approach for sentiment classification of online reviews

Autor: R. M. Chandrasekaran, G. Vinodhini

Publikováno v: Journal of King Saud University: Computer and Information Sciences, Vol 28, Iss 1, Pp 2-12 (2016)

The aim of sentiment classification is to efficiently identify the emotions expressed in the form of text messages. Machine learning methods for sentiment classification have been extensively studied, due to their predominant classification performan

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0d3550c5cad31cca7b3e7cfe55232d1

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Opinion mining using principal component analysis based ensemble model for e-commerce application

Autor: G. Vinodhini, R. M. Chandrasekaran

Publikováno v: CSI Transactions on ICT. 2:169-179

With the rapid expansion of e-commerce over the decades, more and more product reviews emerge on e-commerce sites. In order to effectively utilize the information available in the form of reviews, an automatic opinion mining system is needed to organ

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::42689a98469a2059b390d7e98e8c25ca
https://doi.org/10.1007/s40012-014-0055-3

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Measuring the quality of hybrid opinion mining model for e-commerce application

Autor: R. M. Chandrasekaran, G. Vinodhini

Publikováno v: Measurement. 55:101-109

With the rapid expansion of e-commerce over the decades, the growth of the user generated content in the form of reviews is enormous on the Web. A need to organize the e-commerce reviews arises to help users and organizations in making an informed de

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bee5f1ce0875bc622148c3dc49796221
https://doi.org/10.1016/j.measurement.2014.04.033

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