代码搜索：Classifier

找到约 4,824 项符合「Classifier」的源代码

代码结果 4,824
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cpp extendabledata.cpp

/* * This file is part of MultiBoost, a multi-class * AdaBoost learner/classifier * * Copyright (C) 2005-2006 Norman Casagrande * For informations write to nova77@gmail.com * * This library is free s
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h inputdata.h

/* * This file is part of MultiBoost, a multi-class * AdaBoost learner/classifier * * Copyright (C) 2005-2006 Norman Casagrande * For informations write to nova77@gmail.com * * This library is free s
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h serialization.h

/* * This file is part of MultiBoost, a multi-class * AdaBoost learner/classifier * * Copyright (C) 2005-2006 Norman Casagrande * For informations write to nova77@gmail.com * * This library is free s
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cpp inputdata.cpp

/* * This file is part of MultiBoost, a multi-class * AdaBoost learner/classifier * * Copyright (C) 2005-2006 Norman Casagrande * For informations write to nova77@gmail.com * * This library is free s
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cpp haardata.cpp

/* * This file is part of MultiBoost, a multi-class * AdaBoost learner/classifier * * Copyright (C) 2005-2006 Norman Casagrande * For informations write to nova77@gmail.com * * This library is free s
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cpp main.cpp

/* * This file is part of MultiBoost, a multi-class * AdaBoost learner/classifier * * Copyright (C) 2005-2006 Norman Casagrande * For informations write to nova77@gmail.com * * This library is free s
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h adaboostmhlearner.h

/* * This file is part of MultiBoost, a multi-class * AdaBoost learner/classifier * * Copyright (C) 2005-2006 Norman Casagrande * For informations write to nova77@gmail.com * * This library is free s
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h defaults.h

/* * This file is part of MultiBoost, a multi-class * AdaBoost learner/classifier * * Copyright (C) 2005-2006 Norman Casagrande * For informations write to nova77@gmail.com * * This library is free s
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m click_points.m

function [patterns, targets, params, region] = click_points(region) %Manually enter points into the workspace ax = region(1:4); h = findobj(findobj('Tag','classifier_GUI'),'Tag','txtNumberPo
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m dlpdda.m

function W = dlpdda(x,nu,usematlab) %DLPDDA Distance Linear Programming Data Description attracted by the Average distance % % W = DLPDDA(D,NU) % % This one-class classifier works directly on th
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