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  • Data Mining Algorithms – Principal Component Analysis

    Principal component analysis (PCA) is a technique used to emphasize the majority of the variation and bring out strong patterns in a dataset. It is often used to make data easy to explore and visualize. It is closely connected to eigenvectors and eigenvalues. A short definition of the algorithm: PCA uses an orthogonal transformation to convert ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on June 2, 2015
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