Principal component analysis (PCA, 주성분분석) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. ( https://en.wikipedia.org/wiki/Principal_component_analysis)
대표적인 Dimension reduction 방법. 서로간에 가장 분산을 크게하는 두개의 축을 찾는다.
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