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Data Analysis and Statistics

主成分分析

Principal Component Analysis

A statistical procedure that uses orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. / 一种统计方法,通过正交变换将一组可能相关的观测变量转换为线性不相关的变量集,称为主成分。

Knowledge type
数学理论
First proposed or discovered
Proposer
Turkey Farm member
Creator
农场主
Last updated
2026-11-06 21:06:41
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Sub-knowledge points

Eigenvalue decompositionSingular value decomposition

Higher-order knowledge points

Multivariate statisticsDimensionality reduction

Main parameters and performance indicators

number of components: number of principal components to retainvariance explained: proportion of total variance captured

Open problems

No unresolved problem recorded yet

Related literature

ranked by community stars
A comparison of PCA, ASCA, and vASCA for enhancing the interpretability of biological Raman spectroscopyOpen source

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Creation and modification trail

1 records
automated knowledge publish农场主2026-11-06 21:06:41

Record title: Principal Component Analysis.