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Evaluation Methods for Breast Cancer Prediction in Machine Learning Field.

Breast cancer is the most common malignant tumor found in women, and there is no cure for advanced breast cancer. Early detection and treatment can effectively improve patient survival. This paper uses five machine learning classification models, namely Support Vector Machine (SVM), Logistic Regress...

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Published in:SHS Web of Conferences Vol. 144; pp. 1 - 5
Main Authors: Zhang, Zirui, Li, Zixuan
Format: Article
Published: EDP Sciences 8/26/022
Online Access:View this record in EBSCOhost
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      dt: 8/26/022
      vid: 144
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      pub: EDP Sciences
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        158850588
        10.1051/shsconf/202214403010
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        atl: Evaluation Methods for Breast Cancer Prediction in Machine Learning Field.
      aug:
        au:
          Zhang, Zirui
          Li, Zixuan
        affil:
          Wenzhou-Kean University, Wenzhou, Zhejiang Province, 325000, China
          University of Nottingham Ningbo China, Ningbo Province, 315000, China
      sug:
      ab: Breast cancer is the most common malignant tumor found in women, and there is no cure for advanced breast cancer. Early detection and treatment can effectively improve patient survival. This paper uses five machine learning classification models, namely Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbors Algorithm (KNN). The training data for the five models are provided by the Wisconsin Breast Cancer Dataset (WBCD). By evaluating and comparing the performance of the five models in accuracy, F1Score, ROC curve, and PR curve, the study finds that LR has the best performance.
      pubtype: Conference Proceedings
      doctype: Article
      src: R
    language: English
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