2021. 5. 26. 16:25ㆍ베이지안 딥러닝
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1. Introduction
probability, random variable, random process, kernel function에 대해서 알아보자
2. Set
set, element, subset, universal set, set operations
disjoint
partition
Cartesian product
power set
cardinality |A|: finite, infinite, countable, uncountable, denumerable (countably infinite)
자연수, 실수는 countable, [0,1]사이의 실수집합은 uncountable
mapping, domain, co-domain, image, range, inverse image
one-to-one=injective, onto=surjective, invertible
3. Measure theory
Sigma field가 없으면 measure를 정의할 수 없다.
measurable space : $(U,B)$
measure space : $(U, B, \mu)$
4. Probability
Probability measure : measure + $\mu(X) = 1$
independent != disjoint, mutually exclusive
5. Random Variable
Probability density function : p.d.f
Conditional expectation, probability $X|Y$
Expectation의 정의
두 분포가 같다는 것은 mean값만 가지고 판단 할 수 없다. n-th momentum을 보고나서 판단한다.(2nd momentum: variance)
Independent => uncorrelated
uncorrelated =\=> independent
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