Abstract The paper provides a practical guide on initialization of the recursive mixture-based clustering of non-negative data. For modeling the non-negative data, mixtures of uniform, exponential, gamma and other distributions can be used. Initialization is known to be an important task for a start of the mixture estimation algorithm. Within the considered recursive approach, the key point of initialization is a choice of initial statistics of the involved prior distributions. The paper describes several initialization techniques for the mentioned types of components that can be beneficial primarily from a practical point of view.


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    Title :

    Practical Initialization of Recursive Mixture-Based Clustering for Non-negative Data


    Contributors:


    Publication date :

    2019-04-18


    Size :

    20 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Recursive Filter Initialization

    RICHARD H. BATTIN / STEVEN R. CROOPNICK / AND JAMES M. HABBE | AIAA | 1972


    Recursive filter initialization.

    Battin, R. H. / Croopnick, S. R. / Habbe, J. M. | NTRS | 1972