Hybrid Approach for Diagnosing Thyroid, Hepatitis, and Breast Cancer Based on Correlation Based Feature Selection and Naïve Bayes

Mohammad Ashraf Ali Bani Ahmad, Girija Chetty, Dat Tran, Dharmendra Sharma

Research output: A Conference proceeding or a Chapter in BookConference contribution

4 Citations (Scopus)

Abstract

Feature selection techniques have become an obvious need for researchers in computer science and many other fields of science. Whether the target research is in medicine, agriculture, business, or industry; the necessity for analysing large amount of data is needed. In Addition to that, finding the most excellent feature selection technique that best satisfies a certain learning algorithm could bring the benefit for researchers. Therefore, we proposed a new method for diagnosing some diseases based on a combination of learning algorithm tools and feature selection techniques. The idea is to obtain a hybrid approach that combines the best performing learning algorithms and the best performing feature selection techniques in regards to three well-known datasets. Experimental result shows that co-ordination between correlation based feature selection method along with Naive Bayse learning algorithm can produce promising results.
Original languageEnglish
Title of host publicationInternational Conference on Neural Information Processing (ICONIP 2012)
Subtitle of host publicationLecture Notes in Computer Science
EditorsTingwen Huang, Zhigang Zeng, Chuangdong Li, Chi Sing Leung
Place of PublicationBerlin, Germany
PublisherSpringer
Pages272-280
Number of pages9
Volume7666
ISBN (Print)9783642344787
DOIs
Publication statusPublished - 2012
Event19th International Conference on Neural Information Processing 2012 - Doha, Doha, Qatar
Duration: 12 Nov 201215 Nov 2012

Conference

Conference19th International Conference on Neural Information Processing 2012
CountryQatar
CityDoha
Period12/11/1215/11/12

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Bani Ahmad, M. A. A., Chetty, G., Tran, D., & Sharma, D. (2012). Hybrid Approach for Diagnosing Thyroid, Hepatitis, and Breast Cancer Based on Correlation Based Feature Selection and Naïve Bayes. In T. Huang, Z. Zeng, C. Li, & C. S. Leung (Eds.), International Conference on Neural Information Processing (ICONIP 2012): Lecture Notes in Computer Science (Vol. 7666, pp. 272-280). Berlin, Germany: Springer. https://doi.org/10.1007/978-3-642-34478-7_34