摘要
The Support Vector Machine (SVM) classification algorithm, recently developed from the machine learning community, was used to diagnose breast cancer. At the same time, the SVM was compared to several machine learning techniques currently used in this field. The classification task involves predicting the state of diseases, using data obtained from the UCI machine learning repository. SVM outperformed k-means cluster and two artificial neural networks on the whole. It can be concluded that nine samples could be mislabeled from the comparison of several machine learning techniques.
| 原文 | English |
|---|---|
| 頁(從 - 到) | 900-907 |
| 頁數 | 8 |
| 期刊 | Journal of Chemical Information and Computer Sciences |
| 卷 | 43 |
| 發行號 | 3 |
| DOIs | |
| 出版狀態 | Published - 5月 2003 |
| 對外發佈 | 是 |
UN SDG
此研究成果有助於以下永續發展目標
-
Good health and well being
指紋
深入研究「Diagnosing breast cancer based on support vector machines」主題。共同形成了獨特的指紋。引用此
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