최대가능도,maximum_likelihood

Difference between r1.16 and the current

@@ -1,12 +1,17 @@
AKA '''최대우도'''

파생 개념:
최대가능도추정, 최대우도추정 maximum likelihood estimation MLE
최대가능도추정, 최대우도추정 maximum likelihood estimation MLE - [[추정,estimation]]
[[최대가능도추정,maximum_likelihood_estimation,MLE]]
Compare: 최소제곱오차 MSE (??) [[평균제곱오차,mean_squared_error,MSE]] 아님?
Compare: 최소제곱오차 MSE (??) [[평균제곱오차,mean_square_error,MSE]] 아님?
// 최소제곱에 대해선 see [[최소제곱,least_square]]
최대가능도방법, 최대우도법 maximum likelihood method
https://encyclopediaofmath.org/wiki/Maximum-likelihood_method
관련:
[[가능도,likelihood]]
= tmp bmks ko =
https://process-mining.tistory.com/93

= tmp towatch =
StatQuest: Probability vs Likelihood
@@ -28,7 +33,8 @@
[[wiki:WpKo:최대가능도_방법]]
[[wiki:WpEn:Maximum_likelihood_estimation]]

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Up: [[가능도,likelihood]]
http://biohackers.net/wiki/MaximumLikelihood

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Up: [[최대,maximum]] [[가능도,likelihood]]



AKA 최대우도

파생 개념:
최대가능도추정, 최대우도추정 maximum likelihood estimation MLE - 추정,estimation
최대가능도추정,maximum_likelihood_estimation,MLE
Compare: 최소제곱오차 MSE (??) 평균제곱오차,mean_square_error,MSE 아님?
// 최소제곱에 대해선 see 최소제곱,least_square
최대가능도방법, 최대우도법 maximum likelihood method
관련:

tmp towatch

StatQuest: Probability vs Likelihood
Maximum Likelihood For the Normal Distribution, step-by-step!
StatQuest: Maximum Likelihood

from 석준희 ML강의

maximum likelihood (ML)
likelihood: probability of observation under a certain model
$l=\prod_{i:y_i=0}\frac1{1+e^{\beta_0+\beta_1x_i}}\prod_{i:y_i=1}\frac{e^{\beta_0+\beta_1x_i}}{1+e^{\beta_0+\beta_1x_i}}$