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Using binary classifiers

  1. Machine Learning A large and fascinating field; there’s much more than what you’ll see in this class!
  2. Linear Separators slide thanks to Ray Mooney
  3. Linear Separators slide thanks to Ray Mooney
  4. Nonlinear Separators slide thanks to Ray Mooney (modified)
  5. Nonlinear Separators Note: A more complex function requires more data to generate an accurate model (sample complexity) slide thanks to Kevin Small (modified) x y
  6. Features for recognizing a chair?
  7. Multiclass Classification Many binary classifiers (“one versus all”) slide thanks to Kevin Small (modified) One multiway classifier
  8. A Machine Learning System slide thanks to Kevin Small (modified) Preprocessing Raw Text Formatted Text
  9. A Machine Learning System Feature Vectors slide thanks to Kevin Small (modified) Preprocessing Feature Extraction Raw Text Formatted Text
  10. A Machine Learning System Testing Examples Feature Vectors Training Examples slide thanks to Kevin Small (modified) Preprocessing Feature Extraction Machine Learner Classifier Postprocessing Raw Text Formatted Text Function Parameters Labels Annotated Text
  11. A Machine Learning System Testing Examples Feature Vectors Training Examples slide thanks to Kevin Small (modified) Preprocessing Feature Extraction Machine Learner Classifier Postprocessing Raw Text Formatted Text Function Parameters Labels Annotated Text

Notas del editor

  1. Add function formula
  2. pictures of a 4 class classifier...with the OvA definition
  3. Well-posed learning problems
  4. Framing the classification task
  5. note that the sentence changed
  6. note that the sentence changed
  7. Text categorization
  8. Word tagging
  9. Without algorithmic details as Dan says
  10. A machine learning system
  11. Preprocessing text
  12. A machine learning system
  13. Feature Generation (Kernels)
  14. A machine learning system
  15. A machine learning system
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