Implementation of the EM algorithm for mixtures of Gaussians. Cluster means are initiated by randomly drawing from a uniform distribution and with standard deviations as a fixed fraction of the range of each variable. Model is trained and evaluated on the provided wine dataset.
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Implementation of the EM algorithm for mixtures of Gaussians. Cluster means are initiated by randomly drawing from a uniform distribution and with standard deviations as a fixed fraction of the range of each variable. Model is trained and evaluated on the provided wine dataset.
nbayindirli/gaussian_mixture_models
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Implementation of the EM algorithm for mixtures of Gaussians. Cluster means are initiated by randomly drawing from a uniform distribution and with standard deviations as a fixed fraction of the range of each variable. Model is trained and evaluated on the provided wine dataset.
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