By Andrey V. Savchenko
A unified method for categorizing a number of complex
objects is gifted during this e-book. via likelihood idea, novel
asymptotically minimax standards appropriate for useful functions in imaging
and facts research are tested together with the targeted situations equivalent to the
Jensen-Shannon divergence and the probabilistic neural community. An optimal
approximate nearest neighbor seek set of rules, which permits faster
classification of databases is featured. tough set idea, sequential analysis
and granular computing are used to enhance functionality of the hierarchical
classifiers. functional examples in face id (including deep neural
networks), remoted instructions reputation in voice keep watch over method and
classification of visemes captured through the Kinect intensity digicam are included.
This process creates quick and actual seek approaches by utilizing exact
probability densities of utilized dissimilarity measures.
book can be utilized as a consultant for self sufficient examine and as supplementary material
for a technically orientated graduate path in clever platforms and data
mining. scholars and researchers attracted to the theoretical and practical
aspects of clever category structures will locate solutions to:
- Why traditional implementation of the naive Bayesian
approach doesn't paintings good in snapshot classification?
- the best way to take care of inadequate functionality of hierarchical
- Is it attainable to avoid an exhaustive seek of the
nearest neighbor in a database?
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Search Techniques in Intelligent Classification Systems (SpringerBriefs in Optimization) by Andrey V. Savchenko