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标题:Similarity-based attribute weighting methods via clustering algorithms in the classification of imbalanced medical datasets
时间:2019-10-09 22:50:24
DOI:10.1007/s00521-018-3471-8
大小:2694 kb
页数:28 PAGES
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目录:
  • Similarity-based attribute weighting methods via clustering algorithms in the classification of imbalanced medical datasets
    • Abstract
    • Introduction
    • Imbalanced and nonlinear separable medical datasets
      • Thoracic surgery dataset
      • Parkinson disease dataset
      • Hepatitis disease dataset
      • Pima Indians disease dataset
      • Single proton emission computed tomography (SPECT) heart disease dataset
    • Method
      • The proposed attribute weighting methods
      • Random subsampling
      • Classification algorithms
        • k-NN classifier
        • Random forest classifier
        • Linear discriminant analysis (LDA)
        • Support vector machines (SVM)
    • The experimental results and discussion
      • The performance evaluation metrics
      • The results
    • Conclusions and future work
    • References

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