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/191902/8417115
txt feature_selection.txt
Genetic_Culling@%groups, Out_dim, classifier, classifier params@[0.1,2,'LS',[]]@S
HDR@Out dimension@2@S
ICA@Out dimension, Convergence rate:@[2, 1e-30]@S
Koller@Out dimension@2@S
MDS@Method, Out
www.eeworm.com/read/289336/8558578
m fld.m
function model = fld(data)
% FLD Fisher Linear Discriminat.
%
% Synopsis:
% model = fld(data)
%
% Description:
% This function computes the binary linear classifier based
% on the Fisher Linear Dis
www.eeworm.com/read/289336/8558591
m~ fld.m~
function model = fld(data)
% FLD Fisher Linear Discriminat.
%
% Synopsis:
% model = fld( data )
%
% Description:
% This function computes the binary linear classifier based
% on the Fisher Linear D
www.eeworm.com/read/289334/8558637
m adaclass.m
function [y,dfce] = adaclass(X,model)
% ADACLASS AdaBoost classifier.
%
% Synopsis:
% [y,dfce] = adaclass(X,model)
%
% Description:
% This function implements the AdaBoost classifier which
% its di
www.eeworm.com/read/431675/8662219
m setclass.m
%SETCLASS Set classifier bit of mapping
function w = setclass(w,classbit)
if classbit ~= 0 & classbit ~= 1
error('Mapping classifier bit should be 0 or 1')
end
w.s = classbit;
if classbit & (w.c) ==
www.eeworm.com/read/386050/8767376
m prex_logdens.m
%PREX_LOGDENS PRTools example on density based classifier improvement
%
% This example shows the use and results of LOGDENS for improving
% the classification in the tail of the distributions
h
www.eeworm.com/read/386050/8768108
m svcinfo.m
%SVCINFO More information on Support Vector Classifiers
%
% [W,J,C,NU,ALGINF] = SVC(A,KERNEL,C,OPTIONS)
% W = A*SVC([],KERNEL,C,OPTIONS)
% [W,J,NU,C,ALGINF] = NUSVC(A,KERNEL
www.eeworm.com/read/428849/8834644
m adaclass.m
function [y,dfce] = adaclass(X,model)
% ADACLASS AdaBoost classifier.
%
% Synopsis:
% [y,dfce] = adaclass(X,model)
%
% Description:
% This function implements the AdaBoost classifier which
% its di