代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
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www.eeworm.com/read/426679/9004383
m nflclassifier.m
% Nearest Feature Line Classifier-NFL
function [NFLCrate]=NFLclassifier(features,test_features,trnum,tenum,classnum)
% features the matrix that training samples projected on feature subspace
www.eeworm.com/read/365739/9849751
m average_precision.m
function Average_Precision=Average_precision(Outputs,test_target)
%Computing the average precision
%Outputs: the predicted outputs of the classifier, the output of the ith instance for the jth class
www.eeworm.com/read/365739/9849762
m ranking_loss.m
function RankingLoss=Ranking_loss(Outputs,test_target)
%Computing the hamming loss
%Outputs: the predicted outputs of the classifier, the output of the ith instance for the jth class is stored in Ou
www.eeworm.com/read/362246/10010326
m~ train_ocr.m~
% TRAIN_OCR Training of OCR classifier based on multiclass SVM.
%
% Description:
% The following steps are performed:
% - Training set is created from data in directory ExamplesDir.
% - Mult
www.eeworm.com/read/362246/10010333
m train_ocr.m
% TRAIN_OCR Training of OCR classifier based on multiclass SVM.
%
% Description:
% The following steps are performed:
% - Training set is created from data in directory ExamplesDir.
% - Mult
www.eeworm.com/read/360995/10070082
m incsvdd.m
%INCSVDD Incremental Support Vector Classifier
%
% W = INCSVDD(A,FRACERR,KTYPE,PAR)
%
% Use the incremental version of the SVDD. The kernel is defined by
% KTYPE, with the free parameter PAR. See
www.eeworm.com/read/280595/10312190
m train_ocr.m
% TRAIN_OCR Training of OCR classifier based on multiclass SVM.
%
% Description:
% The following steps are performed:
% - Training set is created from data in directory ExamplesDir.
% - Mult
www.eeworm.com/read/160518/10522501
m bayesc.m
%BAYESC Bayes classifier
%
% W = BAYESC(WA,WB, ... ,P,LABLIST)
%
% INPUT
% WA, WB, ... Trained mappings for supplying class density estimates
% P Vector with class prior probabili
www.eeworm.com/read/160517/10522534
m getcost.m
%GETCOST Get classification cost matrix
%
% [COST,LABLIST] = GETCOST(W)
%
% Returns the classification cost matrix as set in the classifier W.
% An empty cost matrix is interpreted as equal costs for
www.eeworm.com/read/418695/10935156
m invsigm.m
%INVSIGM Inverse sigmoid map
%
% W = W*invsigm
% B = invsigm(A)
%
% Inverse sigmoidal transformation from classifier to map, transforming
% posterior probabilities into distances.
%
% See also da