"주성분 분석"의 두 판 사이의 차이
둘러보기로 가기
검색하러 가기
imported>Pythagoras0 (→memo) |
imported>Pythagoras0 |
||
| 13번째 줄: | 13번째 줄: | ||
==computational resource== | ==computational resource== | ||
* https://drive.google.com/file/d/0B8XXo8Tve1cxT0hBUmdPLUd1VHM/view | * https://drive.google.com/file/d/0B8XXo8Tve1cxT0hBUmdPLUd1VHM/view | ||
| + | * https://jakevdp.github.io/PythonDataScienceHandbook/05.09-principal-component-analysis.html | ||
| + | |||
| + | |||
[[분류:계산]] | [[분류:계산]] | ||
2020년 2월 2일 (일) 13:56 판
introduction
- The principal components of matrix are linear transformations of the original columns into uncorrelated columns arranged in order of decreasing variance
memo
- https://math.stackexchange.com/questions/3869/what-is-the-intuitive-relationship-between-svd-and-pca
- https://mathematica.stackexchange.com/questions/50987/principal-components-how-to-obtain-linear-transformations
- https://stats.stackexchange.com/questions/2691/making-sense-of-principal-component-analysis-eigenvectors-eigenvalues