Breast cancer disease classification using fuzzy-ID3 algorithm based on association function

Nur Farahaina, Idris and Mohd Arfian, Ismail and Mohd Saberi, Mohamad and Shahreen, Kasim and Zalmiyah, Zakaria and Sutikno, Tole (2022) Breast cancer disease classification using fuzzy-ID3 algorithm based on association function. IAES International Journal of Artificial Intelligence, 11 (2). pp. 448-461. ISSN 2089-4872. (Published)

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Breast cancer is the second leading cause of mortality among female cancer patients worldwide. Early detection of breast cancer is considerd as one of the most effective ways to prevent the disease from spreading and enable human can make correct decision on the next process. Automatic diagnostic methods were frequently used to conduct breast cancer diagnoses in order to increase the accuracy and speed of detection. The fuzzy-ID3 algorithm with association function implementation (FID3-AF) is proposed as a classification technique for breast cancer detection. The FID3-AF algorithm is a hybridisation of the fuzzy system, the iterative dichotomizer 3 (ID3) algorithm, and the association function. The fuzzy-neural dynamic-bottleneck-detection (FUZZYDBD) is considered as an automatic fuzzy database definition method, would aid in the development of the fuzzy database for the data fuzzification process in FID3-AF. The FID3-AF overcame ID3’s issue of being unable to handle continuous data. The association function is implemented to minimise overfitting and enhance generalisation ability. The results indicated that FID3-AF is robust in breast cancer classification. A thorough comparison of FID3-AF to numerous existing methods was conducted to validate the proposed method’s competency. This study established that the FID3-AF performed well and outperform other methods in breast cancer classification.

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Association function; Breast cancer; Fuzzy ID3; Fuzzy system; ID3 algorithm
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
T Technology > TA Engineering (General). Civil engineering (General)
Faculty/Division: Institute of Postgraduate Studies
Faculty of Computing
Depositing User: Mr Muhamad Firdaus Janih@Jaini
Date Deposited: 09 Nov 2022 07:09
Last Modified: 09 Nov 2022 07:09
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