代码搜索：One-Class
找到约 293 项符合「One-Class」的源代码
代码结果 293
www.eeworm.com/read/397097/8069115
readme
Data Description Matlab toolbox. (version 0.9)
This toolbox is an add-on to the PRTools toolbox. The toolbox contains
algorithms to train, investigate, visualize and evaluate one-class
classifier
www.eeworm.com/read/397111/8067331
m setthres.m
function out = setthres(w,thr)
%SETTHRES Set the threshold for a one-class classifier
%
% out = setthres(w,thr)
%
% The data of classifier w is copied to classifier out, only the
% threshold value
www.eeworm.com/read/397097/8069133
m contents.m
%Data Description Toolbox (version 0.8)
%
%Dataset construction
%--------------------
%oc_set change normal classif. problem to one-class problem
%target_class extracts the target class
www.eeworm.com/read/397097/8069163
m setthres.m
function out = setthres(w,thr)
%SETTHRES Set the threshold for a one-class classifier
%
% out = setthres(w,thr)
%
% The data of classifier w is copied to classifier out, only the
% threshold value is
www.eeworm.com/read/386050/8769492
m gencirc.m
%GENCIRC Generation of a one-class circular dataset
%
% A = GENCIRC(N,S)
%
% INPUT
% N Size of dataset (optional; default: 50)
% S Standard deviation (optional; default: 0.1)
%
% OUTPUT
%
www.eeworm.com/read/360995/10069940
m random_dd.m
%RANDOM_DD Random one-class classifier
%
% W = RANDOM_DD(A,FRACREJ)
%
% This is the trivial one-class classifier, randomly assigning labels
% and rejecting FRACREJ of the data objects. This pr
www.eeworm.com/read/299984/7140698
m gencirc.m
%GENCIRC Generation of a one-class circular dataset
%
% A = GENCIRC(N,S)
%
% INPUT
% N Size of dataset (optional; default: 50)
% S Standard deviation (optional; default: 0.1)
%
% OUTPUT
%
www.eeworm.com/read/460435/7251174
m gencirc.m
%GENCIRC Generation of a one-class circular dataset
%
% A = GENCIRC(N,S)
%
% INPUT
% N Size of dataset (optional; default: 50)
% S Standard deviation (optional; default: 0.1)
%
% OUTPUT
%
www.eeworm.com/read/451547/7461928
m random_dd.m
%RANDOM_DD Random one-class classifier
%
% W = RANDOM_DD(A,FRACREJ)
%
% This is the trivial one-class classifier, randomly assigning labels
% and rejecting FRACREJ of the data objects. This pr
www.eeworm.com/read/450608/7480568
m gencirc.m
%GENCIRC Generation of a one-class circular dataset
%
% A = GENCIRC(N,S)
%
% INPUT
% N Size of dataset (optional; default: 50)
% S Standard deviation (optional; default: 0.1)
%
% OUTPUT
%