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Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution...

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Bayesian Learning Note: The core of the material presented here has been borrowed from the slides prepared by Pedro Domingos. Minor customization has been done to suit the specific needs of the course.
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Page 1: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which

Bayesian Learning

Note: The core of the material presented here has been borrowed from the slides prepared by Pedro Domingos. Minor customization has been done to suit the specific needs of the course.

Page 2: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 3: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 4: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 5: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 6: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 7: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 8: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 9: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 10: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 11: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 12: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 13: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 14: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 15: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 16: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 17: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 18: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 19: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 20: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 21: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 22: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 23: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 24: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 25: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 26: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 27: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 28: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 29: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 30: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 31: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 32: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 33: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 34: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 35: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 36: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 37: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which
Page 38: Bayesian Learning - cs.ashoka.edu.incs.ashoka.edu.in/CS303/Lectures/bayes.pdf · Typical solution is m-estimate for P (ai Ivj) nc + mp where n is number of training examples for which

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