주성분분석,principal_component_analysis,PCA

주성분분석,principal_component_analysis,PCA (rev. 1.13)

많은 양의 데이터를 데이터를 본질을 해치지 않는 저차원으로 압축하는 것
Method for compressing a lot of data into something that captures the essence of the original data

한국어 설명:
https://angeloyeo.github.io/2019/07/27/PCA.html
https://darkpgmr.tistory.com/110

mklink
고유값,eigenvalue
고유벡터,eigenvector
공분산행렬,covariance_matrix curr see 공분산,covariance

tmp links ko ¶

http://t-robotics.blogspot.com/2018/02/32-pca.html

tmp links en ¶

Principal Component Analysis Explained Visually
https://setosa.io/ev/principal-component-analysis/
https://news.ycombinator.com/item?id=27017675

Twins ¶

주성분_분석

tmp video{
StatQuest: Principal Component Analysis 주성분 분석 (PCA)
https://www.youtube.com/watch?v=FgakZw6K1QQ

KU김성범
https://www.youtube.com/watch?v=FhQm2Tc8Kic
}

Compare:
독립성분분석,independent_component_analysis,ICA
{
한국어 설명
https://angeloyeo.github.io/2020/07/14/ICA.html
에 의하면 중심극한정리,central_limit_theorem,CLT를 반대로 한 개념이라고.

}

주성분_분석_PCA

Up: 자료,data??

분석,analysis > 다변량분석,multivariate_analysis