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E9 205 Machine Learning for Signal Processing Probablistic Linear - PowerPoint PPT Presentation

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E9 205 Machine Learning for Signal Processing Probablistic Linear Models 30-09-2019 Linear Models for Classification Optimize a modified cost function Bishop - PRML book (Chap 3) Least Squares for Classification K-class classification

  1. E9 205 Machine Learning for Signal Processing Probablistic Linear Models 30-09-2019

  2. Linear Models for Classification ❖ Optimize a modified cost function Bishop - PRML book (Chap 3)

  3. Least Squares for Classification ❖ K-class classification problem ❖ With 1-of-K hot encoding, and least squares regression Bishop - PRML book (Chap 3)

  4. Logistic Regression ❖ 2- class logistic regression ❖ Maximum likelihood solution ❖ K-class logistic regression ❖ Maximum likelihood solution Bishop - PRML book (Chap 3)

  5. Least Squares versus Logistic Regression Bishop - PRML book (Chap 4)

  6. Least Squares versus Logistic Regression Bishop - PRML book (Chap 4)

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