Stochastic Outlier Selection
Read OriginalThis technical blog article by Jeroen Janssens explains Stochastic Outlier Selection (SOS), a machine learning algorithm for outlier detection. It details how SOS works by transforming data into a dissimilarity matrix, computing affinities and binding probabilities, and outputting an outlier probability for each point. The article discusses its relation to t-SNE, its perplexity parameter, and includes a link to a Python implementation.
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