代码搜索：classification

找到约 3,679 项符合「classification」的源代码

代码结果 3,679
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m getbias.m

function bias = getbias(net) % GETBIAS % % Accessor method returning the bias of a support vector classification % network. % % bias = getbias(net); % % File : @svc/getbias.m %
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www.eeworm.com/read/140850/13059589

m svctutor.m

function tutor = svctutor(arg) % SVCTUTOR % % Constructor for a class of tutor objects used to train support vector % classification networks. Note this is an abstract base class, you cannot %
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www.eeworm.com/read/316604/13520394

m genetic_programming.m

function [D, best_fun] = genetic_programming(features, targets, params, region) % A genetic programming algorithm for classification % % features - Train features % targets - Train targets
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www.eeworm.com/read/307651/13718047

m dosom.m

% doSom: Supervised classification using Self-Organizing Map (SOM is % actually an unsupervised clustering technique. ) % % [C] = doSom(data, proto, protoClass) % % Input and output argument
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www.eeworm.com/read/128684/5980327

m getbias.m

function bias = getbias(net) % GETBIAS % % Accessor method returning the bias of a support vector classification % network. % % bias = getbias(net); % % File : @svc/getbias.m %
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www.eeworm.com/read/128684/5980349

m svctutor.m

function tutor = svctutor(arg) % SVCTUTOR % % Constructor for a class of tutor objects used to train support vector % classification networks. Note this is an abstract base class, you cannot %
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www.eeworm.com/read/359185/6352483

m genetic_programming.m

function [D, best_fun] = genetic_programming(features, targets, params, region) % A genetic programming algorithm for classification % % features - Train features % targets - Train targets
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www.eeworm.com/read/493206/6398461

m genetic_programming.m

function [D, best_fun] = genetic_programming(features, targets, params, region) % A genetic programming algorithm for classification % % features - Train features % targets - Train targets
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www.eeworm.com/read/486842/6530644

c prind.c

/* Weight-setting and scoring implementation for PrInd classification (Fuhr's Probabilistic Indexing) */ /* Copyright (C) 1997, 1998, 1999 Andrew McCallum Written by: Andrew Kachites McCallum
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www.eeworm.com/read/485544/6552789

m demtrain.m

function demtrain(action); %DEMTRAIN Demonstrate training of MLP network. % % Description % DEMTRAIN brings up a simple GUI to show the training of an MLP % network on classification and regression pr
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