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Principal Components Analysis

Principal Components Analysis. Jan Sobotka ( sobotj 1@fel.cvut.cz). PCA Algorithm. Statistical technique PCA was invented in 1901 by Karl Pearson Is a technique used to reduce multidimensional data sets to lower dimensions

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Principal Components Analysis

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  1. IBM - CVUT Student Research Projects Principal Components Analysis Jan Sobotka (sobotj1@fel.cvut.cz)

  2. PCA Algorithm • Statistical technique • PCA was invented in 1901 by Karl Pearson • Is a technique used to reduce multidimensional data sets to lower dimensions • PCA is mathematically defined as an orthogonal linear transformation that transforms the data to a new coordinate system IBM - CVUT Student Research Projects 2

  3. PCA Usage • Useful statistical technique • Data compression • Computer Vision • Face recognition • Finding patterns in data IBM - CVUT Student Research Projects 3

  4. PCA in six steps • Get some data • Substract the mean • Calculate covariance matrix • Calculate the eigenvectors and eigenvalues of the covariance matrix • Choosing components and forming a feature vector • Deriving the new data set IBM - CVUT Student Research Projects 4

  5. My implementation • Obtain information and sources about Cell and PCA • Write code for PPU unit • Port kernel of computation to one SPU unit • Optimize computation on one SPU IBM - CVUT Student Research Projects 5

  6. IBM - CVUT Student Research Projects Thank you for your attention

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