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/213240/15139965
m dlpdd.m
function W = dlpdd(x,nu,usematlab)
%DLPDD Distance Linear Programming Data Description
%
% W = DLPDD(D,NU)
%
% This one-class classifier works directly on the distance (dissimilarity)
% matrix
www.eeworm.com/read/204456/15339262
m dlpdd.m
function W = dlpdd(x,nu,usematlab)
%DLPDD Distance Linear Programming Data Description
%
% W = DLPDD(D,NU)
%
% This one-class classifier works directly on the distance (dissimilarity)
% matrix
www.eeworm.com/read/360995/10069963
m dd_ex9.m
% Show the crossvalidation procedure
%
% Generate some simple data, split it in training and testing data using
% 10-fold cross-validation, and compare several one-class classifiers on
% it.
% Copyri
www.eeworm.com/read/360995/10070003
m dlpdda.m
function W = dlpdda(x,nu,usematlab)
%DLPDDA Distance Linear Programming Data Description attracted by the Average distance
%
% W = DLPDDA(D,NU)
%
% This one-class classifier works directly on th
www.eeworm.com/read/360995/10070092
m multic.m
%MULTIC Make a multi-class classifier
%
% W = MULTIC(A,V)
%
% Train the (untrained!) one-class classifier V on each of the classes
% in A, and combine it to a multi-class classifier W. If an object
www.eeworm.com/read/451547/7461939
m dd_ex9.m
% Show the crossvalidation procedure
%
% Generate some simple data, split it in training and testing data using
% 10-fold cross-validation, and compare several one-class classifiers on
% it.
% Copyri
www.eeworm.com/read/451547/7461954
m dlpdda.m
function W = dlpdda(x,nu,usematlab)
%DLPDDA Distance Linear Programming Data Description attracted by the Average distance
%
% W = DLPDDA(D,NU)
%
% This one-class classifier works directly on th
www.eeworm.com/read/451547/7461980
m multic.m
%MULTIC Make a multi-class classifier
%
% W = MULTIC(A,V)
%
% Train the (untrained!) one-class classifier V on each of the classes
% in A, and combine it to a multi-class classifier W. If an object
www.eeworm.com/read/397111/8067115
m gendatout.m
function z = gendatout(a,n,dR)
%GENDATOUT Generate outlier objects
%
% Z = GENDATOUT(A,N)
%
% Generate N outlier objects in a hypersphere round dataset A. This
% dataset should be a one-class da
www.eeworm.com/read/397111/8067132
m dlpdd.m
function W = dlpdd(x,nu,usematlab)
%DLPDD Distance Linear Programming Data Description
%
% W = DLPDD(X,NU)
%
% This linear one-class classifier works directly on the distances, so
% the data is