代码搜索：classification

找到约 3,679 项符合「classification」的源代码

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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/128468/14295396

m contents.m

% Statistical Pattern Recognition Toolbox. % % Contents % % bayes - (dir) Bayes classification. % datasets - (dir) Functions for handling with data sets. % generalp - (dir) General purpose
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www.eeworm.com/read/128193/14311424

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/128193/14311478

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/122800/14667790

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/222301/14697754

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/222301/14697795

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/220289/14843878

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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www.eeworm.com/read/212307/15160156

m gp_classify.m

% GP_classify: implementation for Gaussian Process for Classification % % Parameters: % para: parameters % 1. PriorMean: mean of the prior distribution, default: 0 % 2. PriorVariance: varian
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www.eeworm.com/read/212307/15160188

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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