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/213240/15140016
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/204456/15339298
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/204456/15339313
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/386050/8767317
m prex_density.m
%PREX_DENSITY Various density plots
%
% Prtools example to show the use of density estimators and how to
% visualize them.
help prex_density
delfigs
figure
echo on
% Generate one-class data
a =
www.eeworm.com/read/360995/10069861
m lpdd.m
%LPDD Linear programming distance data description
%
% W = LPDD(X,NU,S,DTYPE,P)
%
% One-class classifier put into a linear programming framework. From
% the data X the distance matrix is comp
www.eeworm.com/read/360995/10069908
m stump_dd.m
%STUMP_DD Threshold one dim. one-class classifier
%
% W = STUMP_DD(A,FRACREJ,DIM)
%
% Put a threshold on one of the feature dimensions DIM of dataset A. The
% threshold is put such that a frac
www.eeworm.com/read/159921/10588158
c m2o_sor.c
/*---------------------------------------------------------------------------
[Alpha,bias,kercnt] = m2o_sor(data,labels,ker,arg,C,eps)
M2O_SOR Multi-class translated to one-class SVM and solved by
www.eeworm.com/read/421949/10676839
c m2o_sor.c
/*---------------------------------------------------------------------------
[Alpha,bias,kercnt] = m2o_sor(data,labels,ker,arg,C,eps)
M2O_SOR Multi-class translated to one-class SVM and solved by
www.eeworm.com/read/451547/7461885
m lpdd.m
%LPDD Linear programming distance data description
%
% W = LPDD(X,NU,S,DTYPE,P)
%
% One-class classifier put into a linear programming framework. From
% the data X the distance matrix is comp
www.eeworm.com/read/451547/7461909
m stump_dd.m
%STUMP_DD Threshold one dim. one-class classifier
%
% W = STUMP_DD(A,FRACREJ,DIM)
%
% Put a threshold on one of the feature dimensions DIM of dataset A. The
% threshold is put such that a frac