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Machine learning approximation techniques using dual trees
Ergashbaev, Denis
Pujol Vila, Oriol
This master thesis explores a dual-tree framework as applied to a particular class of machine learning problems that are collectively referred to as generalized n-body problems. It builds a new algorithm on top of it and improves existing Boosted OGE classifier.
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
Machine learning
Artificial intelligence
kd-tree
classification
characterizing boundary points
ensemble of classifiers
Gabriel neighboring rule
Aprenentatge automàtic
Intel·ligència artificial
info:eu-repo/semantics/masterThesis
Universitat Politècnica de Catalunya
         

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