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/474600/6813576
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:
www.eeworm.com/read/415313/11076741
m train_test_multiple_class.m
% Train_Test_Multiple_Class: multi-class learning wrapper for binary
% classifiers
%
% Pararmeters:
% classifier: the base classifier
% para: parameters
% 1. CodeType: multi-class coding type
www.eeworm.com/read/411674/11233909
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/204456/15339338
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/386050/8768108
m svcinfo.m
%SVCINFO More information on Support Vector Classifiers
%
% [W,J,C,NU,ALGINF] = SVC(A,KERNEL,C,OPTIONS)
% W = A*SVC([],KERNEL,C,OPTIONS)
% [W,J,NU,C,ALGINF] = NUSVC(A,KERNEL
www.eeworm.com/read/386050/8769017
m plotc.m
%PLOTC Plot classifiers
%
% PLOTC(W,S,LINE_WIDTH)
% PLOTC(W,LINE_WIDTH,S)
%
% Plots the discriminant as given by the mapping W on predefined axis,
% typically set by scatterd. Discriminants are
www.eeworm.com/read/386050/8769521
m featselv.m
%FEATSELV Varying feature selection
%
% W = FEATSELV(A)
% W = A*FEATSELV
%
% Selects all features with a non-zero variance.
% Classifiers can be trained like A*(FEATSELV*LDC([],1E-3)) to make
www.eeworm.com/read/299984/7140314
m svcinfo.m
%SVCINFO More information on Support Vector Classifiers
%
% [W,J,C,NU,ALGINF] = SVC(A,KERNEL,C,OPTIONS)
% W = A*SVC([],KERNEL,C,OPTIONS)
% [W,J,NU,C,ALGINF] = NUSVC(A,KERNEL
www.eeworm.com/read/299984/7140556
m plotc.m
%PLOTC Plot classifiers
%
% PLOTC(W,S,LINE_WIDTH)
% PLOTC(W,LINE_WIDTH,S)
%
% Plots the discriminant as given by the mapping W on predefined axis,
% typically set by scatterd. Discriminants are
www.eeworm.com/read/460435/7250789
m svcinfo.m
%SVCINFO More information on Support Vector Classifiers
%
% [W,J,C,NU,ALGINF] = SVC(A,KERNEL,C,OPTIONS)
% W = A*SVC([],KERNEL,C,OPTIONS)
% [W,J,NU,C,ALGINF] = NUSVC(A,KERNEL