Variables {principal component} (PC) can be linear-descriptor combinations. Unsupervised linear method {principal component analysis, factor} (PCA) represents data as product of score matrix, for original observations, and loading-matrix transform, for original factors. PCA is factor-analysis method in which linear variable combinations make two or three new variables. PCA reduces unimportant variables.
Physical Sciences>Chemistry>Biochemistry>Drug>Activity>Methods>Factor Analysis
5-Chemistry-Biochemistry-Drug-Activity-Methods-Factor Analysis
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Date Modified: 2022.0224