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Videos by Random walk distances in data clustering and applications

  • Random walk distances in data clustering and applications
    Anastasios Matzavinos

    Clustering data into groups of similarity is well recognized as an important step in many diverse applications, including biomedical imaging, data mining and bioinformatics. Well known clustering methods, dating to the 70's and 80's, include the K-means algorithm and its generalization, the Fuzzy C-means (FCM) scheme, and hierarchical tree decompositions...

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