Read about pca | 3 Discussions | Page 1

  1. C

    I Differences between the PCA function and Karhunen-Loève expansion

    Hello everyone. I am currently using the pca function from matlab on a gaussian process. Matlab's pca offers three results. Coeff, Score and Latent. Latent are the eigenvalues of the covariance matrix, Coeff are the eigenvectors of said matrix and Score are the representation of the original...
  2. R

    I Using PCA for variable reduction

    In the textbook “Principal Component Analysis” Jolliffe (§9.2) suggests the following method for variable reduction: “When the variables fall into well-defined clusters, there will be one high-variance PC and, except in the case of 'single-variable' clusters, one or more low-variance PCs...
  3. D

    Java Eigenword embeddings and spectral learning; I'm a beginner...

    Hi everyone, I am a mathematics undergraduate and I'm currently doing an internship at the informatics department of a university. I am well and truly out of my depth. My supervisor has assigned me tasks which include Java (a language I'm having to quickly pick up, having only used python/R)...
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