代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
代码结果 4,824
www.eeworm.com/read/451547/7461983
m is_occ.m
%IS_OCC True for one-class classifiers
%
% IS_OCC(W) returns true if the classifier W is a one-class classifier,
% outputting only classes 'target' and/or 'outlier' and having a
% structure with t
www.eeworm.com/read/441018/7677900
m contents.m
% OSU Support Vector Machines (SVMs) Toolbox
% version 3.00, Feb. 2002
%
% The core of this toolbox is based on Dr. Lin's Lib SVM version 2.33
% For more details, please see:
% http://www.csie.n
www.eeworm.com/read/299459/7850447
m knnrule.m
function model=knnrule(data,K)
% KNNRULE Creates K-nearest neighbours classifier.
%
% Synopsis:
% model=knnrule(data)
% model=knnrule(data,K)
%
% Description:
% It creates model of the K-nearest ne
www.eeworm.com/read/299459/7850867
m fldqp.m
function model = fldqp(data)
% FLDQP Fisher Linear Discriminat using Quadratic Programming.
%
% Synopsis:
% model = fldqp( data )
%
% Description:
% This function computes the binary linear classifi
www.eeworm.com/read/399158/7885638
m contents.m
% OSU Support Vector Machines (SVMs) Toolbox
% version 3.00, Feb. 2002
%
% The core of this toolbox is based on Dr. Lin's Lib SVM version 2.33
% For more details, please see:
% http://www.csie.n
www.eeworm.com/read/397761/8023062
m display.m
function display(net)
fprintf(1,'\nsupport vector classifier:\n\n');
fprintf(1,' kernel = %s\n', char(net.kernel));
fprintf(1,' bias = %f\n', net.bias);
fprintf(1,' sv = %s\n', m
www.eeworm.com/read/397111/8067310
m is_occ.m
%IS_OCC True for one-class classifiers
%
% IS_OCC(W) returns true if the classifier W is a one-class classifier,
% outputting only classes 'target' and/or 'outlier' and having a
% structure with t
www.eeworm.com/read/397097/8069158
m is_occ.m
%IS_OCC True for one-class classifiers
%
% is_occ(w) returns true if the classifier w is a one-class classifier,
% outputting only classes 'target' and/or 'outlier' and having a
% structure with t
www.eeworm.com/read/140853/13058108
m contents.m
% OSU Support Vector Machines (SVMs) Toolbox
% version 3.00, Feb. 2002
%
% The core of this toolbox is based on Dr. Lin's Lib SVM version 2.33
% For more details, please see:
% http://www.csie.n
www.eeworm.com/read/312163/13617447
m knnrule.m
function model=knnrule(data,K)
% KNNRULE Creates K-nearest neighbours classifier.
%
% Synopsis:
% model=knnrule(data)
% model=knnrule(data,K)
%
% Description:
% It creates model of the K-nearest ne