Výsledky vyhledávání - "Sengupta, Shampa"

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Single Reduct Generation Based on Relative Indiscernibility of Rough Set Theory

In real world everything is an object which represents particular classes. Every object can be fully described by its attributes. Any real world dataset contains large number of attributes and objects. Classifiers give poor performance when these hug

Externí odkaz: http://arxiv.org/abs/1203.3170

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Akademický článek

Development of a Rice Plant Disease Classification Model in Big Data Environment.

Autor: Sengupta, Shampa¹ (AUTHOR), Dutta, Abhijit² (AUTHOR) abhijit_me2005@yahoo.co.in, Abdelmohsen, Shaimaa A. M.³ (AUTHOR), Alyousef, Haifa A.³ (AUTHOR), Rahimi-Gorji, Mohammad⁴ (AUTHOR)

Publikováno v: Bioengineering (Basel). Dec2022, Vol. 9 Issue 12, p758. 14p.

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Akademický článek

A group incremental feature selection for classification using rough set theory based genetic algorithm

Autor: Das, Asit K., Sengupta, Shampa, Bhattacharyya, Siddhartha

Publikováno v: In Applied Soft Computing Journal April 2018 65:400-411

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Akademický článek

Particle Swarm Optimization based incremental classifier design for rice disease prediction

Autor: Sengupta, Shampa, Das, Asit K.

Publikováno v: In Computers and Electronics in Agriculture August 2017 140:443-451

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Design of an Intelligent System for Diabetes Prediction by Integrating Rough Set Theory and Genetic Algorithm

Autor: Sengupta, Shampa, Pal, Kumud Ranjan, Garg, Vivek

Publikováno v: Designing Intelligent Healthcare Systems, Products, and Services Using Disruptive Technologies and Health Informatics ISBN: 9781003217107

Diabetes causes a lot of damage to the internal organs and body parts. To find out the primary symptoms or features to detect and prevent the disease from its severity, an intelligent healthcare system is needed to analyse the disease data to save th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4d948b506e6553e5827b04b4b265593
https://doi.org/10.1201/9781003217107-9

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Periodical

Development of rough-TOPSIS algorithm as hybrid MCDM and its implementation to predict diabetes

Autor: Sengupta, Shampa, Datta, Debabrata, Rajest, S. Suman, Paramasivan, P., Shynu, T., Regin, R.

Publikováno v: International Journal of Bioinformatics Research and Applications; 2023, Vol. 19 Issue: 4 p252-279, 28p

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Periodical

Reproductive rights and disability rights through an intersectional analysis

Autor: Jain, Dipika, Sengupta, Shampa

Publikováno v: Jindal Global Law Review; December 2021, Vol. 12 Issue: 2 p337-357, 21p

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Kniha

Reduct Generation by Formation of Directed Minimal Spanning Tree Using Rough Set Theory.

Autor: Das, Asit Kumar, Sengupta, Shampa, Chakrabarty, Saikat

Publikováno v: Proceedings of the International Conference on Information Systems Design & Intelligent Applications 2012 (INDIA 2012) held in Visakhapatnam, India, January 2012; 2012, p127-135, 9p

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Kniha

Formation of a Compact Reduct Set Based on Discernibility Relation and Attribute Dependency of Rough Set Theory.

Autor: Das, Asit Kumar, Chakrabarty, Saikat, Sengupta, Shampa

Publikováno v: Wireless Networks & Computational Intelligence (9783642316852); 2012, p253-261, 9p

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Kniha

Dimension Reduction Using Clustering Algorithm and Rough Set Theory.

Autor: Sengupta, Shampa, Das, Asit Kumar

Publikováno v: Swarm, Evolutionary & Memetic Computing (9783642353796); 2012, p705-712, 8p

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