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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m k_l_classifier.m

% M-file function, K_L_Classifier.m % 判断第k个样本属于g1和g2中的哪一类 % X 样本向量组 % k 样本位于第k个位置 % m1 第1组均值 % s1 第1组协方差 % P1 第1组先验概率 % m2 第2组均值 % s2 第2组协方差 % P2 第2组先验概率 % c 判断结果该样本属于g1或g2 function c
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www.eeworm.com/read/13871/284295

m mixgauss_classifier_apply.m

function [classHatTest, probPos] = mixgauss_classifier_apply(mixgauss, testFeatures) Bpos = mixgauss_prob(testFeatures, mixgauss.pos.mu, mixgauss.pos.Sigma, mixgauss.pos.prior); Bneg = mixgauss_pr
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www.eeworm.com/read/13871/284312

m mixgauss_classifier_train.m

function mixgauss = mixgauss_classifier_train(trainFeatures, trainLabels, nc, varargin) % function mixgauss = mixgauss_classifier_train(trainFeatures, trainLabels, nclusters, varargin) % trainFeatur
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www.eeworm.com/read/457053/1601312

tcl ns-mpls-classifier.tcl

# -*- Mode:tcl; tcl-indent-level:8; tab-width:8; indent-tabs-mode:t -*- # # Time-stamp: # # Copyright (c) 1997 by the University of Southern California # All rights res
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www.eeworm.com/read/455269/1624882

tcl ns-mpls-classifier.tcl

# -*- Mode:tcl; tcl-indent-level:8; tab-width:8; indent-tabs-mode:t -*- # # Time-stamp: # # Copyright (c) 1997 by the University of Southern California # All rights res
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www.eeworm.com/read/213708/4913356

tcl ns-mpls-classifier.tcl

# -*- Mode:tcl; tcl-indent-level:8; tab-width:8; indent-tabs-mode:t -*- # # Time-stamp: # # Copyright (c) 1997 by the University of Southern California # All rights res
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www.eeworm.com/read/205961/5013543

java classifier2info.java

/* Copyright (C) 2003 Univ. of Massachusetts Amherst, Computer Science Dept. This file is part of "MALLET" (MAchine Learning for LanguagE Toolkit). http://www.cs.umass.edu/~mccallum/mallet Th
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www.eeworm.com/read/193974/5138854

java classifier2info.java

/* Copyright (C) 2003 Univ. of Massachusetts Amherst, Computer Science Dept. This file is part of "MALLET" (MAchine Learning for LanguagE Toolkit). http://www.cs.umass.edu/~mccallum/mallet Th
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www.eeworm.com/read/175689/5343377

asv e_kernel_classifier.asv

% load input data trn = load('riply_trn'); subplot(3,1,1);title('原始分布1');cla; h1=ppatterns(trn); legend([h1],'Training set'); % train kernel PCA by greedy algorithm options = struct('ker','rbf
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www.eeworm.com/read/175689/5343379

m e_kernel_classifier.m

figure('name','特征提取_KernelClassfier'); % load input data trn = load('riply_trn'); subplot(3,1,1);title('原始分布1');cla; h1=ppatterns(trn); legend([h1],'Training set'); % train kernel PCA by g
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