代码搜索：objects
找到约 10,000 项符合「objects」的源代码
代码结果 10,000
www.eeworm.com/read/493294/6399859
m spatm.m
%SPATM Augment image dataset with spatial label information
%
% E = SPATM(D,S)
% E = D*SPATM([],S)
%
% INPUT
% D image dataset classified by a classifier
% S smoothing parameter
www.eeworm.com/read/493294/6399899
m target_class.m
function [a,b] = target_class(a,clnr)
% TARGET_CLASS extracts the target class from an one-class dataset
%
% A = TARGET_CLASS(A,CLNR)
%
% Extract the target class from an one-class dataset. When t
www.eeworm.com/read/493294/6399941
m knnc.m
%KNNC K-Nearest Neighbor Classifier
%
% [W,K,E] = KNNC(A,K)
% [W,K,E] = KNNC(A)
%
% INPUT
% A Dataset
% K Number of the nearest neighbors (optional; default: K is
% optimized with resp
www.eeworm.com/read/493294/6400328
m find_target.m
%FIND_TARGET extract the indices of the target and outlier objects
%
% [It,Io] = FIND_TARGET(A)
%
% Return the indices of the objects from dataset A which are labeled
% 'target' and 'outlier' i
www.eeworm.com/read/493294/6400339
m incsvdd.m
function W = incsvdd(a,fracerr,ktype,par,kfunction)
%INCSVDD Incremental Support Vector Classifier
%
% W = INCSVDD(A,FRACERR,KTYPE,PAR)
%
% Use the incremental version of the SVDD. The kernel is d
www.eeworm.com/read/493127/6406865
tra memory.tra
*** Creating Trace Output File '.\Obj\Memory.tra' Ok.
### Preparing for ADS-LD.
### Creating ADS-LD Command Line
### List of Objects: adding '".\obj\lpc2300.o"'
### List of Objects: adding '".\obj
www.eeworm.com/read/492890/6411725
tra ucosii.tra
*** Creating Trace Output File '.\APP\Output\uCOSii.tra' Ok.
### Preparing for ADS-LD.
### Creating ADS-LD Command Line
### List of Objects: adding '".\app\output\app.o"'
### List of Objects: addi
www.eeworm.com/read/492400/6422208
m target_class.m
function [a,b] = target_class(a,clnr)
% TARGET_CLASS extracts the target class from an one-class dataset
%
% A = TARGET_CLASS(A,CLNR)
%
% Extract the target class from an one-class dataset. When t
www.eeworm.com/read/492400/6422291
m find_target.m
%FIND_TARGET extract the indices of the target and outlier objects
%
% [It,Io] = FIND_TARGET(A)
%
% Return the indices of the objects from dataset A which are labeled
% 'target' and 'outlier' i
www.eeworm.com/read/492400/6422295
m incsvdd.m
function W = incsvdd(a,fracerr,ktype,par,kfunction)
%INCSVDD Incremental Support Vector Classifier
%
% W = INCSVDD(A,FRACERR,KTYPE,PAR)
%
% Use the incremental version of the SVDD. The kernel is d