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/223154/14651900
m contents.m
% BIOSIG/T400 contains classifiers.
%
% LDBC linear discriminant based classifier
% MDBC mahalanobis distance based classifier
% LLBC log-likelihood based classifier
% GDBC general distance
www.eeworm.com/read/213492/15133783
m demo_linclass.m
function result = demo_linclass(action,hfigure,varargin)
% DEMO_LINCLASS Demo on the algorithms learning linear classifiers.
%
% Synopsis:
% demo_linclass
%
% Description:
% DEMO_LINCLASS demonstrat
www.eeworm.com/read/213240/15140043
m is_occ.m
%IS_OCC True for one-class classifiers
%
% IS_OCC(W) returns true if the classifier W is a one-class classifier,
% outputting only classes 'target' and/or 'outlier' and having a
% structure with t
www.eeworm.com/read/175689/5343410
asv demo_linclass.asv
function result = demo_linclass(action,hfigure,varargin)
% DEMO_LINCLASS Demo on the algorithms learning linear classifiers.
%
% Synopsis:
% demo_linclass
%
% Description:
% DEMO_LINCLASS demonstrat
www.eeworm.com/read/175689/5343416
m demo_linclass.m
function result = demo_linclass(action,hfigure,varargin)
% DEMO_LINCLASS Demo on the algorithms learning linear classifiers.
%
% Synopsis:
% demo_linclass
%
% Description:
% DEMO_LINCLASS demonstrat
www.eeworm.com/read/347796/3163027
java codematrix.java
package dragon.ir.classification.multiclass;
/**
* Code Matrix Interface
* The code matrix handle the problem of how to build a set of binary classifiers for multi-class classification. A
www.eeworm.com/read/268397/4252865
java codematrix.java
package dragon.ir.classification.multiclass;
/**
* Code Matrix Interface
* The code matrix handle the problem of how to build a set of binary classifiers for multi-class classification. A
www.eeworm.com/read/428780/1954084
asv demo_linclass.asv
function result = demo_linclass(action,hfigure,varargin)
% DEMO_LINCLASS Demo on the algorithms learning linear classifiers.
%
% Synopsis:
% demo_linclass
%
% Description:
% DEMO_LINCLASS demonstrat
www.eeworm.com/read/428780/1954090
m demo_linclass.m
function result = demo_linclass(action,hfigure,varargin)
% DEMO_LINCLASS Demo on the algorithms learning linear classifiers.
%
% Synopsis:
% demo_linclass
%
% Description:
% DEMO_LINCLASS demonstrat
www.eeworm.com/read/386597/2570224
m components_with_df.m
function [test_targets, errors] = Components_with_DF(train_patterns, train_targets, test_patterns, Ncomponents)
% Classify points using component classifiers with discriminant functions
% Inputs: