代码搜索：classification
找到约 3,679 项符合「classification」的源代码
代码结果 3,679
www.eeworm.com/read/316944/13514015
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/312163/13617307
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/312163/13617315
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 - (
www.eeworm.com/read/134901/5891495
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/128684/5980332
m fwd.m
function y = fwd(net,x)
% FWD
%
% Compute the output of a multi-class support vector classification network.
%
% y = fwd(net, x);
%
% where x is a matrix of input patterns, where each colu
www.eeworm.com/read/128684/5980372
m fwd.m
function y = fwd(net,x)
% FWD
%
% Compute the output of a multi-class support vector classification network.
%
% y = fwd(net, x);
%
% where x is a matrix of input patterns, where each colu
www.eeworm.com/read/128684/5980374
m fwd.m
function y = fwd(net, x)
% FWD
%
% Compute the output of a dag-svm multi-class support vector classification
% network.
%
% y = fwd(net, x);
%
% where x is a matrix of input patterns, in
www.eeworm.com/read/126765/6012317
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/101066/6256598
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/487309/6518995
m probclass.m
%PROBCLASS Classification based on conditional pdfs
%function [dataclass,dataprobs]=probclass(data,v1,v2,pdftbl)
%Get probabilities (dataprobs) and most likely class (dataclass)
%data: data point to b