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Imbalanced Data Assessment.pdf

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Preview of Imbalanced Data Assessment
🔗 Source: eva.fing.edu.uy
📊 Size: 651 KB
📄 Pages: 13 pages
⬇️ Downloads: 492

Summary

The article discusses the challenges of evaluating models on imbalanced data sets, where one class has a significantly larger number of examples than the other. It highlights the limitations of traditional evaluation measures such as accuracy and introduces alternative measures, including G-means, likelihood ratios, F-Measure, Youden index, and Matthews correlation coefficient, as well as graphical performance assessment methods like ROC curves and lift charts. These measures aim to provide a more credible evaluation of models on imbalanced data sets, particularly in applications like churn prediction, credit card fraud detection, and medical diagnosis.

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Description

The article discusses the challenges of evaluating models on imbalanced data sets, where one class has a significantly larger number of examples than the...

Technical Information

  • File Format: PDF
  • File Size: 651 KB
  • Pages: 13
  • Language: EN
  • Total Downloads: 492
  • Last Updated: 3 hours ago

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This PDF document about Imbalanced Data Assessment provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Imbalanced Data Assessment.

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