Data Analysis and Statistics
主成分分析
Principal Component AnalysisA 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
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 starsA comparison of PCA, ASCA, and vASCA for enhancing the interpretability of biological Raman spectroscopyOpen source
Related products and links
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Creation and modification trail
1 recordsRecord title: Principal Component Analysis.
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