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Lecture 2. Bayesian Decision Theory

Bayes Decision. It is the decision making when all underlying probability distributions are known.It is optimal given the distributions are known.For two classes w1 and w2 , Prior probabilities for an unknown new observation:P(w1) : the new observation belongs to class 1P(w2) : the new obs

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Lecture 2. Bayesian Decision Theory

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    1. Lecture 2. Bayesian Decision Theory

    2. Bayes Decision

    3. Bayes Decision

    4. Bayes Decision

    5. Bayes Decision

    6. Loss function

    7. Loss function

    8. Loss function

    9. Loss function

    10. Loss function

    11. Loss function

    12. Discriminant function & decision surface

    13. Decision surface

    14. Minimax

    15. Normal density

    17. Normal density

    18. Normal density

    19. Discriminant function for normal density

    20. Discriminant function for normal density

    21. Discriminant function for normal density

    23. Discriminant function for normal density

    24. Discriminant function for normal density

    25. Discriminant function for normal density

    26. Discriminant function for normal density

    27. Discriminant function for normal density

    28. Discriminant function for normal density

    29. Discriminant function for normal density

    30. Discriminant function for discrete features

    33. Optimality

    34. Optimality

    35. Optimality

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