Researchers have developed a novel, computationally efficient method for estimating the number of components in Gaussian mixture models, particularly effective for high-dimensional and imbalanced datasets. The technique involves centering the data, calculating singular values, and applying a threshold, bypassing traditional iterative or likelihood-based approaches. This method demonstrates consistent accuracy even when the data dimension exceeds the sample size and can process large datasets rapidly, with one example showing it handling ten million samples in one hundred dimensions within a minute. AI
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RANK_REASON The submission is an academic paper on a statistical machine learning method.
