Information gain and adaptive neuro-fuzzy inference system for breast cancer diagnoses

Muhammad Ashraf, Kim Le, Xu Huang

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

9 Citations (Scopus)
18 Downloads (Pure)

Abstract

This paper presents a new approach for breast cancer diagnosis using a combination of an Adaptive Network based Fuzzy Inference System (ANFIS) and the Information Gain method. In this approach, the ANFIS is to build an input-output mapping using both human knowledge and machine learning ability and the information gain method is to reduce the number of input features to ANFIS. An experimental result shows 98.23% accuracy which underlines the capability of the proposed algorithm.
Original languageEnglish
Title of host publicationProceedings: 5th International Conference on Computer Sciences and Convergence Information Technology: ICCIT 2010
Place of PublicationPiscataway, N.J., USA
PublisherIEEE
Pages911-915
Number of pages5
Volume2
ISBN (Print)9788988678305
DOIs
Publication statusPublished - 2010
Event5th ICCIT: 2010 International Conference on Computer Sciences and Convergence Information Technology - Seoul, Korea, Republic of
Duration: 30 Nov 20102 Dec 2010

Conference

Conference5th ICCIT: 2010 International Conference on Computer Sciences and Convergence Information Technology
CountryKorea, Republic of
CitySeoul
Period30/11/102/12/10

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  • Cite this

    Ashraf, M., Le, K., & Huang, X. (2010). Information gain and adaptive neuro-fuzzy inference system for breast cancer diagnoses. In Proceedings: 5th International Conference on Computer Sciences and Convergence Information Technology: ICCIT 2010 (Vol. 2, pp. 911-915). IEEE. https://doi.org/10.1109/ICCIT.2010.5711189