Development of Hepatitis Disease Detection System by Exploiting Sparsity in Linear Support Vector Machine to Improve Strength of AdaBoost Ensemble Model

Joint Authors

Farhan, Muhammad
Javeed, Ashir
Akbar, Wasif
Wu, Wei-ping
Saleem, Sehrish
Saleem, Muhammad Asim
Ali, Liaqat

Source

Mobile Information Systems

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-11-03

Country of Publication

Egypt

No. of Pages

9

Main Subjects

Telecommunications Engineering

Abstract EN

Hepatitis disease is a deadliest disease.

The management and diagnosis of hepatitis disease is expensive and requires high level of human expertise which poses challenges for the health care system in underdeveloped and developing countries.

Hence, development of automated methods for accurate prediction of hepatitis disease is inevitable.

In this paper, we develop a diagnostic system which hybridizes a linear support vector machine (SVM) model with adaptive boosting (AdaBoost) model.

We exploit sparsity in linear SVM that is caused by L1 regularization.

The sparse L1-regularized SVM is capable of eliminating redundant or irrelevant features from feature space.

After filtering features through the sparse linear SVM, the output of the SVM is applied to the AdaBoost ensemble model which is used for classification purposes.

Two types of numerical experiments are performed on the clinical features of hepatitis disease collected from UCI machine learning repository.

In the first experiment, only conventional AdaBoost model is used, while in the second experiment, a feature vector is applied to the sparse linear SVM before its application to the AdaBoost model.

Simulation results demonstrate that the strength of a conventional AdaBoost model is enhanced by 6.39% by the proposed method, and its time complexity is also reduced.

In addition, the proposed method shows better performance than many previously developed methods for hepatitis disease prediction.

American Psychological Association (APA)

Akbar, Wasif& Wu, Wei-ping& Saleem, Sehrish& Farhan, Muhammad& Saleem, Muhammad Asim& Javeed, Ashir…[et al.]. 2020. Development of Hepatitis Disease Detection System by Exploiting Sparsity in Linear Support Vector Machine to Improve Strength of AdaBoost Ensemble Model. Mobile Information Systems،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1192561

Modern Language Association (MLA)

Farhan, Muhammad…[et al.]. Development of Hepatitis Disease Detection System by Exploiting Sparsity in Linear Support Vector Machine to Improve Strength of AdaBoost Ensemble Model. Mobile Information Systems No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1192561

American Medical Association (AMA)

Akbar, Wasif& Wu, Wei-ping& Saleem, Sehrish& Farhan, Muhammad& Saleem, Muhammad Asim& Javeed, Ashir…[et al.]. Development of Hepatitis Disease Detection System by Exploiting Sparsity in Linear Support Vector Machine to Improve Strength of AdaBoost Ensemble Model. Mobile Information Systems. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1192561

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1192561