代码搜索：classifiers
找到约 2,305 项符合「classifiers」的源代码
代码结果 2,305
www.eeworm.com/read/450608/7480426
m stacked.m
%STACKED Combining classifiers in the same feature space
%
% WC = STACKED(W1,W2,W3, ....) or WC = [W1,W2,W3, ...]
% WC = STACKED({W1,W2,W3, ...}) or WC = [{W1,W2,W3, ...}]
% WC = STACKED(WC,W1,
www.eeworm.com/read/450608/7480431
m clevals.m
%CLEVALS Classifier evaluation (feature size/learning curve), bootstrap possible
%
% E = CLEVALS(A,CLASSF,FEATSIZE,TRAINSIZES,NREPS,T,FID)
%
% INPUT
% A Training dataset
% CLASSF Cl
www.eeworm.com/read/450608/7480449
m reject.m
%REJECT Compute the error-reject trade-off curve
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% E = REJECT(D);
% E = REJECT(A,W);
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% INPUT
% D Classification result, D = A*W
% A Dataset
% W Cell array of trained classifiers
www.eeworm.com/read/441245/7672604
m medianc.m
%MEDIANC Median combining classifier
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% W = MEDIANC(V)
% W = V*MEDIANC
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% INPUT
% V Set of classifiers
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% OUTPUT
% W Median combining classifier on V
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% DESCRIPTION
% If V = [V
www.eeworm.com/read/441245/7672664
m averagec.m
%AVERAGEC Combining of linear classifiers by averaging coefficients
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% W = AVERAGEC(V)
% W = V*AVERAGEC
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% INPUT
% V A set of affine base classifiers.
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% OUTPUT
% W Combined classifier.
%
%
www.eeworm.com/read/441245/7672704
m prodc.m
%PRODC Product combining classifier
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% W = PRODC(V)
% W = V*PRODC
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% INPUT
% V Set of classifiers trained on the same classes
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% OUTPUT
% W Product combiner
%
% DESCRIPTION
% It def
www.eeworm.com/read/441245/7673028
m meanc.m
%MEANC Mean combining classifier
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% W = MEANC(V)
% W = V*MEANC
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% INPUT
% V Set of classifiers (optional)
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% OUTPUT
% W Mean combiner
%
% DESCRIPTION
% If V = [V1,V2,V3, ... ] is a s
www.eeworm.com/read/441245/7673044
m cleval.m
%CLEVAL Classifier evaluation (learning curve)
%
% E = CLEVAL(A,CLASSF,TRAINSIZES,NREPS,T,TESTFUN)
%
% INPUT
% A Training dataset
% CLASSF Classifier to evaluate
% TRAINSIZE Vect
www.eeworm.com/read/441245/7673048
m clevalb.m
%CLEVALB Classifier evaluation (learning curve), bootstrap version
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% E = CLEVALB(A,CLASSF,TRAINSIZES,N)
%
% INPUT
% A Training dataset
% CLASSF Classifier to evaluate
% TRAINS
www.eeworm.com/read/441245/7673223
m stacked.m
%STACKED Combining classifiers in the same feature space
%
% WC = STACKED(W1,W2,W3, ....) or WC = [W1,W2,W3, ...]
% WC = STACKED({W1,W2,W3, ...}) or WC = [{W1,W2,W3, ...}]
% WC = STACKED(WC,W1,