稀疏主成分分析SPCA(R语言)

Principal component analysis (PCA) is widely used in data processing and dimensionality

reduction. However, PCA suffffers from the fact that each principal component is a linear combi

nation of all the original variables, thus it is often diffiffifficult to interpret the results. We introduce

a new method called sparse principal component analysis (SPCA)