代码搜索：classification
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www.eeworm.com/read/353640/3084012
c isxdigit.c
/* isxdigit.c - character classification and conversion macros */
/* Copyright 1992-1993 Wind River Systems, Inc. */
/*
modification history
--------------------
01e,03mar93,jdi more documentation
www.eeworm.com/read/262046/4315564
c isxdigit.c
/* isxdigit.c - character classification and conversion macros */
/* Copyright 1992-1993 Wind River Systems, Inc. */
/*
modification history
--------------------
01e,03mar93,jdi more documentation
www.eeworm.com/read/474089/6832661
m music.m
function P = music(Y,M,D,Lambda,Angles,Num)
%MUSIC Multiple Signal Classification Method for direction finding.
%
% Usage: P = MUSIC(Y,M,D,Lambda,Angles,Num)
%
%Input parameters:
%
www.eeworm.com/read/172172/9722092
m trainlssvm.m
function [model,b,X,Y] = trainlssvm(model,X,Y)
% Train the support values and the bias term of an LS-SVM for classification or function approximation
%
% >> [alpha, b] = trainlssvm({X,Y,type,gam,ke
www.eeworm.com/read/367440/9748451
m trainlssvm.m
function [model,b,X,Y] = trainlssvm(model,X,Y)
% Train the support values and the bias term of an LS-SVM for classification or function approximation
%
% >> [alpha, b] = trainlssvm({X,Y,type,gam,ke
www.eeworm.com/read/413489/11154154
m step2.m
% step2.m
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% All important data in (cell) array s.
% The first row are s(1,:)centers,then s(2,:)samples,s(3,:)in-class distance!!
% sample classification based on mi
www.eeworm.com/read/413489/11154166
asv step2.asv
% step2.m
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% All important data in (cell) array s.
% The first row are s(1,:)centers,then s(2,:)samples,s(3,:)in-class distance!!
% sample classification based on mi
www.eeworm.com/read/413479/11154361
m step2.m
% step2.m
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% All important data in (cell) array s.
% The first row are s(1,:)centers,then s(2,:)samples,s(3,:)in-class distance!!
% sample classification based on mi
www.eeworm.com/read/411674/11233522
pl references.pl
{
"Anderson62" =>"T.W.Anderson and R.R.Bahadur. Classification into two
multivariate normal distributions with differrentia covariance matrices.
Anals of Mathematical Statistics, 33:420--431, Ju
www.eeworm.com/read/411674/11233536
m contents.m
% Data sets used by the STPRtool.
%
% andersons_task - (dir) Input for demo on Generalized Anderson's task.
% binary_separable - (dir) Input for demo on Linear classification.
% gmm_sample - (