Data Science Cheatsheet 2
Principal Component Analysis Projects data onto orthogonal vectors that maximize variance. Remember, given an n nmatrix A, a nonzero vector ~x, and a scaler , if A~x= ~xthen ~xand are an eigenvector and eigenvalue of A. In PCA, the eigenvectors are uncorrelated and represent principal components. 1.Start with the covariance matrix of ...
Analysis, Principal component analysis, Principal, Component
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