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Pattern Recognition

Pattern Recognition

Pattern Recognition. Probability Review. Why Bother About Probabilities?. Accounting for uncertainty is a crucial component in decision making (e.g., classification) because of ambiguity in our measurements. Probability theory is the proper mechanism for accounting for uncertainty .

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647 views • 49 slides
Advisor ? Dr.Hsu Graduate ? Keng-Wei Chang Author ? Lian Yan and David J. Miller

Advisor ? Dr.Hsu Graduate ? Keng-Wei Chang Author ? Lian Yan and David J. Miller

???????? National Yunlin University of Science and Technology. General statistical inference for discrete and mixed spaces by an approximate application of the maximum entropy principle. Advisor ? Dr.Hsu Graduate ? Keng-Wei Chang Author ? Lian Yan and David J. Miller.

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607 views • 48 slides
Probability Review

Probability Review

Probability Review. CS479/679 Pattern Recognition Dr. George Bebis. Why Bother About Probabilities?. Probability theory is the proper mechanism for accounting for uncertainty .

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650 views • 48 slides
Multiple Discrete Random Variables

Multiple Discrete Random Variables

Multiple Discrete Random Variables. Introduction. Consider the choice of a student at random from a population of college students. We wish to know his/her height, weight, blood pressure, pulse rate, etc.

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613 views • 40 slides
Chapter 4 pp. 153-210

Chapter 4 pp. 153-210

Chapter 4 pp. 153-210. William J. Pervin The University of Texas at Dallas Richardson, Texas 75083. Chapter 3. Pairs of Random Variables. Chapter 4. 4.1 Joint CDF : The joint CDF F X,Y of RVs X and Y is F X,Y (x,y) = P[X ? x, Y ? y]. Chapter 4. 0 ? F X,Y (x,y) ? 1

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310 views • 18 slides
3.4 Independence of random vectors

3.4 Independence of random vectors

3.4 Independence of random vectors. Definition It is said that X is independent of Y for any real number a<b, c<d,p{a<X ? b,c<Y ? d} =p{a<X ? b}p{c<Y ? d},i.e. event{a<X ? b}is independent of {c<Y ? d}.

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148 views • 8 slides

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