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Breast Cancer Prediction Using K-mean Classification Algorithm with Self-adaptive Weight |
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| รหัสดีโอไอ | |
| Creator | Arika Thammano |
| Title | Breast Cancer Prediction Using K-mean Classification Algorithm with Self-adaptive Weight |
| Contributor | Muthita Wangkid, Arit Thammano |
| Publisher | Faculty of Engineering and Technology, Mahanakorn University of Technology |
| Publication Year | 2563 |
| Journal Title | Journal of Information Science and Technology |
| Journal Vol. | 10 |
| Journal No. | 2 |
| Page no. | 1-9 |
| Keyword | Breast cancer, Prediction, Artificial intelligence, Data science, Classification, K-mean algorithm |
| URL Website | https://tci-thaijo.org/index.php/JIST |
| Website title | Journal of Information Science and Technology |
| ISSN | 2651-1053 |
| Abstract | "Breast cancer" is the first-rank non-communicable disease found in women both in Thailand and the world at large. The statistic of the National Cancer Institute reveals that the number of Thai women suffering from breast cancer is likely to increase every year. If breast cancer can be found at its early stage and cured properly, the risk of mortality can be considerably reduced. This research presents K-mean classification algorithm with self-adaptive weight and the program for breast cancer prediction using Python programming language with an aim to help identify and cure the early-stage breast cancer patients in a timely manner. The algorithm presented in this research has been modified from K-mean clustering algorithm to be able to perform the classification task and to have the ability to self-adapt the weights of the features in the Euclidean distance equation. The efficiency of algorithm and breast cancer prediction program was tested using Breast Cancer Coimbra data set. The result shows that the breast cancer prediction using the proposed algorithm is more accurate than other artificial intelligence algorithms. |
