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  • 1
    Book
    Book
    Pattern recognition and machine learning (2006)
    New York, NY : Springer
    Details
    UID:
    kobvindex_GFZ103508
    Format: XX, 738 S. , Ill., graph. Darst.
    ISBN: 0387310738 , 978-0-387-31073-2
    Series Statement: Information science and statistics
    Content: Contents: Introduction. - Probability distributions. - Linear models for regression. - Linear models for classification.- Neural networks.- Kernel methods.- Sparse kernel machines.-Graphical models.- Mixture models and EM.- Approximate inference.- Sampling methods.- Continuous latent variables.- Sequential data.- Combining models.
    Note: MAB0014.001: M 07.0424 , Literaturverz. S. 711 - 728
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