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Paper Title

LIVER DISORDER DETECTION USING FUZZY SUPPORT VECTOR MACHINE

Article Identifiers

Registration ID: IJNRD_191259

Published ID: IJNRD2304290

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Keywords

Fuzzy Svm , Liver disease, Twin Support Vector Machine, G - Mean.

Abstract

The total number of samples in each class varies in real-world binary classification situations. Alcoholism or the effects of viruses have a genetic issue with how the human liver functions. If not found in the early stages, it might cause cancer or liver failure. The suggested method aims to use liver function to identify early liver disorders. The proposed DWTWSVM and DWLSTSVM are compared to support vector machines (SVM), twin SVMs (TWSVM), least squares TWSVMs (LSTWSVM), fuzzy TWSVMs (FTWSVM), improved fuzzy least squares TWSVMs (IFLSTWSVM), and SVM for binary CIL in terms of model performance in terms of F1- score, G-mean, recall, and precision. In order to confirm the viability and application of the proposed models, a statistical research based on F1-score and G-mean on RW datasets is done. In a number of pertinent unbalanced artificial and real-world datasets, the outcomes are quantified using the geometric mean and area under the curve (G- mean) . The outcomes are contrasted with SVM, enhanced fuzzy least squares SVM, fuzzy least squares SVM with randomness, fuzzy least squares SVM with affinity and class probabilities, and fuzzy least squares SVM. The research primarily focuses on the use of fuzzy twin SVMs to the diagnosis of liver disease. In order to confirm the value and applicability of the proposed models, a statistical research based on F1-score and G-mean on RW datasets is carried out.

How To Cite (APA)

B S M MANASA, B HEMA SUSHMA SRI, V MOHAN SAI, R SATYA SAI, & Dr Barenya B. Hazarika,Khoiram Motilal Singh (April-2023). LIVER DISORDER DETECTION USING FUZZY SUPPORT VECTOR MACHINE. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(4), c715-c718. https://ijnrd.org/papers/IJNRD2304290.pdf

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Other Publication Details

Paper Reg. ID: IJNRD_191259

Published Paper Id: IJNRD2304290

Research Area: Engineering

Author Type: Foreign Author

Country: -, -, -

Published Paper PDF: https://ijnrd.org/papers/IJNRD2304290.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304290

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