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function engine = frontier_inf_engine(bnet) % FRONTIER_INF_ENGINE Inference engine for DBNs which which uses the frontier algorithm. % engine = frontier_inf_engine(bnet) % % The frontier algorithm ext

% Algorithms learning linear classifiers from finite vector sets. % % ekozinec - Kozinec's algorithm for eps-optimal separating hyperplane. % ekozinec2 - Kozinec's algorithm for eps-optimal separ

function net = somtrain(net, options, x) %SOMTRAIN Kohonen training algorithm for SOM. % % Description % NET = SOMTRAIN{NET, OPTIONS, X) uses Kohonen's algorithm to train a % SOM. Both on-line and ba

function engine = frontier_inf_engine(bnet) % FRONTIER_INF_ENGINE Inference engine for DBNs which which uses the frontier algorithm. % engine = frontier_inf_engine(bnet) % % The frontier algorithm ext

function engine = frontier_inf_engine(bnet) % FRONTIER_INF_ENGINE Inference engine for DBNs which which uses the frontier algorithm. % engine = frontier_inf_engine(bnet) % % The frontier algorithm ext

% Algorithms learning linear classifiers from finite vector sets. % % ekozinec - Kozinec's algorithm for eps-optimal separating hyperplane. % ekozinec2 - Kozinec's algorithm for eps-optimal separ

Genetic Algorithm M-files Last modified: January 24, 1994 Written by: Andrew F. Potvin The MathWorks, Inc. email: potvin@mathwork.com The main genetic algorithm M-fil

/* peano.c */ /* copyright Ken Musgrave */ /* June 1986 */ /* * space-filling peano curve algorithm. * fills n-space with a 1-D peano curve. * * the algorithm is utterly incomprehensible, * so

The GA Playground: TSP Test Problem Bayg29 handled by genetic algorithm

The GA Playground: TSP Test Problem Att48 handled by genetic algorithm