Principal Component Analysis
  • Method description:
  • Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables (entities each of which takes on various numerical values) into a set of values of linearly uncorrelated variables called principal components.

    Installation: online;

    Dependent libraries: sklearn;

    QR code:

    • 依赖库文件:sklearn