Hi,
The formula for PCA is X=UV, where X is a pxn matrix (columns: observations; rows: variables), U (the coeff matrix) is a pxp matrix, and V (scores) is a pxn matrix. However, in Matlab the input should be transposed (this is, a nxp matrix, where columns are the variables, and not observations). I wonder why the consistency of the original formula was changed. Thank you.

댓글 수: 2

Walter Roberson
Walter Roberson 2017년 11월 12일
"Consider a data matrix, X, with column-wise zero empirical mean (the sample mean of each column has been shifted to zero), where each of the n rows represents a different repetition of the experiment, and each of the p columns gives a particular kind of feature (say, the results from a particular sensor)."
That is columns as variables and rows as observations, the same order that MATLAB uses.
Tahariet Sharon
Tahariet Sharon 2017년 11월 13일
Thanks you, Walter. So if X is time x sensors, then COEFF is time x PCs?

댓글을 달려면 로그인하십시오.

답변 (0개)

카테고리

도움말 센터File Exchange에서 Dimensionality Reduction and Feature Extraction에 대해 자세히 알아보기

질문:

2017년 11월 12일

댓글:

2017년 11월 13일

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by