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Fusion: Practice and Applications
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Title

Randomized Vector Network Model for Thyroid Prediction Using Relief And Lasso Feature Selection Approaches

  Maruthi Prasad 1 * ,   Santhosh R. 2

1  Department of Computer Science and Engineering, Faculty of Engineering, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu, India
    (karpagam.publication@gmail.com)

2  Department of Computer Science and Engineering, Faculty of Engineering, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu, India
    (santhoshrd@gmail.com)

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Doi   :   https://doi.org/10.54216/FPA.120211

Received: January 28, 2023 Revised: April 21, 2023 Accepted: June 25, 2023

Abstract :

The studies’ primary aim is to help the research scholars as a source who would like to research in the thyroid disease detection region. UC Irvin knowledge discovery provides databases files for the machine learning archives' thyroid dataset. Here, a random vector network model (RVNM) is proposed to perform classification tasks. The proposed model integrates the prior dataset information regarding the samples to train the more effective classifier. This cascaded random vector network model helps in thyroid disease prediction. The evaluation process is performed to predict and determine the respective performance concerning accuracy. The intuition is provided in this research, like forecasting the thyroid disease; it also calls attention to the process of using a Randomized Vector Network Model (RVNM) as a medium for classification. The simulation is done in the MATLAB 2020a environment and establishes a better trade-off than various existing approaches. The model gives a prediction accuracy of 96.1% accuracy compared to other models and shows a better trade than others.

Keywords :

Thyroid disease; classification; randomized vector; prediction accuracy; attention

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Cite this Article as :
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MLA Maruthi Prasad, Santhosh R.. "Randomized Vector Network Model for Thyroid Prediction Using Relief And Lasso Feature Selection Approaches." Fusion: Practice and Applications, Vol. 12, No. 2, 2023 ,PP. 132-144 (Doi   :  https://doi.org/10.54216/FPA.120211)
APA Maruthi Prasad, Santhosh R.. (2023). Randomized Vector Network Model for Thyroid Prediction Using Relief And Lasso Feature Selection Approaches. Journal of Fusion: Practice and Applications, 12 ( 2 ), 132-144 (Doi   :  https://doi.org/10.54216/FPA.120211)
Chicago Maruthi Prasad, Santhosh R.. "Randomized Vector Network Model for Thyroid Prediction Using Relief And Lasso Feature Selection Approaches." Journal of Fusion: Practice and Applications, 12 no. 2 (2023): 132-144 (Doi   :  https://doi.org/10.54216/FPA.120211)
Harvard Maruthi Prasad, Santhosh R.. (2023). Randomized Vector Network Model for Thyroid Prediction Using Relief And Lasso Feature Selection Approaches. Journal of Fusion: Practice and Applications, 12 ( 2 ), 132-144 (Doi   :  https://doi.org/10.54216/FPA.120211)
Vancouver Maruthi Prasad, Santhosh R.. Randomized Vector Network Model for Thyroid Prediction Using Relief And Lasso Feature Selection Approaches. Journal of Fusion: Practice and Applications, (2023); 12 ( 2 ): 132-144 (Doi   :  https://doi.org/10.54216/FPA.120211)
IEEE Maruthi Prasad, Santhosh R., Randomized Vector Network Model for Thyroid Prediction Using Relief And Lasso Feature Selection Approaches, Journal of Fusion: Practice and Applications, Vol. 12 , No. 2 , (2023) : 132-144 (Doi   :  https://doi.org/10.54216/FPA.120211)
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