代码搜索：explained
找到约 346 项符合「explained」的源代码
代码结果 346
www.eeworm.com/read/137160/13342352
m klldc.m
%KLLDC Linear classifier built on the KL expansion of the common covariance matrix
%
% W = KLLDC(A,N)
% W = KLLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of significant eigenvectors
% AL
www.eeworm.com/read/314653/13562266
m pcldc.m
%PCLDC Linear classifier using PC expansion on the joint data.
%
% W = PCLDC(A,N)
% W = PCLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of eigenvectors
% ALF Total explained variance (defau
www.eeworm.com/read/314653/13562563
m klldc.m
%KLLDC Linear classifier built on the KL expansion of the common covariance matrix
%
% W = KLLDC(A,N)
% W = KLLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of significant eigenvectors
% AL
www.eeworm.com/read/493294/6399985
m pcldc.m
%PCLDC Linear classifier using PC expansion on the joint data.
%
% W = PCLDC(A,N)
% W = PCLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of eigenvectors
% ALF Total explained variance (defau
www.eeworm.com/read/493294/6400324
m klldc.m
%KLLDC Linear classifier built on the KL expansion of the common covariance matrix
%
% W = KLLDC(A,N)
% W = KLLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of significant eigenvectors
% AL
www.eeworm.com/read/483741/6593294
txt userguide.txt
You may find the current version of the userguide at:
http://www.flashloaded.com/userguides/3dbox
Note: The use of the files "3D BoxLive.swf" and "3D BookLive.swf" are explained in the on-line use
www.eeworm.com/read/483741/6593553
txt userguide.txt
You may find the current version of the userguide at:
http://www.flashloaded.com/userguides/3dplane
Note: The use of the file "3D PlaneLive.swf" is explained in the on-line userguide.
www.eeworm.com/read/400577/11572675
m pcldc.m
%PCLDC Linear classifier using PC expansion on the joint data.
%
% W = PCLDC(A,N)
% W = PCLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of eigenvectors
% ALF Total explained variance (defau
www.eeworm.com/read/255755/12057363
m pcldc.m
%PCLDC Linear classifier using PC expansion on the joint data.
%
% W = PCLDC(A,N)
% W = PCLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of eigenvectors
% ALF Total explained variance (defau
www.eeworm.com/read/255755/12058001
m klldc.m
%KLLDC Linear classifier built on the KL expansion of the common covariance matrix
%
% W = KLLDC(A,N)
% W = KLLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of significant eigenvectors
% AL