代码搜索:classification

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m~ contents.m~

% Algorithms to solve the Generalized Anderson's task. % % andrerr - Classification error of the Generalized Anderson's task. % androrig - Original method to solve the Anderson's task. % ean
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m getnsv.m

function nsv = getnsv(net) % GETNSV % % Accessor method returning the number of support vectors of a support vector % classification network. % % n = getnsv(net); % % File : @dags
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m dagsvm.m

function net = dagsvm(arg) % PAIRWISE % % Construct a dag-svm multi-class support vector classification network. % % Examples: % % % default constructor (a 0-class dagsvm network!) % %
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m getnsv.m

function nsv = getnsv(net) % GETNSV % % Accessor method returning the number of support vectors of a support vector % classification network. % % n = getnsv(net); % % File : @dags
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m dagsvm.m

function net = dagsvm(arg) % PAIRWISE % % Construct a dag-svm multi-class support vector classification network. % % Examples: % % % default constructor (a 0-class dagsvm network!) % %
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html classifier.html

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html package-use.html

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html package-use.html

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m lmnc.m

%LMNC Levenberg-Marquardt trained feed-forward neural net classifier % % [W,HIST] = LMNC (A,UNITS,ITER,W_INI,T,FID) % % INPUT % A Dataset % UNITS Array indicating number of units in each
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m lmnc.m

%LMNC Levenberg-Marquardt trained feed-forward neural net classifier % % [W,HIST] = LMNC (A,UNITS,ITER,W_INI,T,FID) % % INPUT % A Dataset % UNITS Array indicating number of units in each