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An implementation of PPCA by following the paper of Michael E. Tipping and Christopher M. Bishop

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gkagkos/Probabilistic-PCA

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Probabilistic-PCA

Authors: Polydefkis Gkagkos, Leonidas Valavanis, Kai Ma

Implementation of Probabilistic Principal Component Analysis.
About: An implementation of PPCA by following the paper of Michael E. Tipping and Christopher M. Bishop.
Dataset_Generator.py : Generate random Dataset, CIFAR10, MNIST.
Utils.py : Contain functions that are used for the pre-proccessing of data.
PPCA.py : Implementation of PPCA with expectation maximazations. Also some tries on Maximum Likelihood but still incomplete.
Main.py : Main file that runs the code. KernelPCA.py : Implementation of Kernel PCA (incomplete).

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An implementation of PPCA by following the paper of Michael E. Tipping and Christopher M. Bishop

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