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Efficient EM Training of Gaussian Mixtur...
Delalleau, Olivier...

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Efficient EM Training of Gaussian Mixtures with Missing Data by Delalleau, Olivier ( Author )
Lemonjar Open Access
Australian National University
27-07-2023
In data-mining applications, we are frequently faced with a large fraction of missing entries in the data matrix, which is problematic for most discriminant machine learning algorithms. A solution that we explore in this paper is the use of a generative model (a mixture of Gaussians) to compute the conditional expectation of the missing variables given the observed variables. Since training a Gaussian mixture with many different patterns of missing values can be computationally very expensive, we introduce a spanning-tree based algorithm that significantly speeds up training in these conditions. We also observe that good results can be obtained by using the generative model to fill-in the missing values for a separate discriminant learning algorithm.
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Article
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29.34 KB
English
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MYR 0.01
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http://arxiv.org/abs/1209.0521
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