Machine Learning for Imbalanced Data: Tackle imbalanced datasets using machine learning and deep learning techniques

by Kumar Abhishek - Machine Learning for Imbalanced Data Reviews Summary

Ratings Breakdown

Rated 5 by 8 people

Pros from Reviews

  • Sampling methods
  • Cost-sensitive learning
  • Threshold adjustment
  • Model calibration
  • Coverage of sampling techniques
  • Practical approach
  • Extensive coverage of evaluation metrics
  • Comprehensive coverage of preprocessing techniques

Cons from Reviews

    None found

Notable Features

Tackle Imbalanced Datasets
Machine Learning Techniques
Deep Learning Techniques
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