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/351797/10609859
m pairwise.m
function net = pairwise(arg)
% PAIRWISE
%
% Construct a pairwise multi-class support vector classification network.
%
% Examples:
%
% % default constructor (a 0-class pairwise network!)
%
www.eeworm.com/read/421949/10676314
m code_ecoc.m
function [codebook,scheme] = code_ECOC(m,dist,distfct)
% Generate the codebook for multiclass classification with Error Correcting Output encoding if feasible.
%
% function coding the multiple classes
www.eeworm.com/read/421949/10676542
m contents.m
% Bayes Classification.
%
% bayeserr - Computes the Bayesian risk for optimal classifier.
% bayescln - Classifier based on Bayes decision rule for Gaussians.
% bayesnd - Discrim. function, dic
www.eeworm.com/read/420350/10800893
m eigenface.m
% An experiment on the eigenface recognition
% You may separate training and classification processes.
%
% Input
% (cell) Xt c cell of D x Ni matrix which contains a training data
%
www.eeworm.com/read/420350/10800902
m fisherface.m
% An experiment on the fisherface recognition
% You may separate training and classification processes.
%
% Input
% (cell) Xt c cell of D x Ni matrix which contains a training data
%
www.eeworm.com/read/418695/10935176
m gendats.m
%GENDATS Generation of a simple classification problem
%
% A = gendats(na,nb,k,d)
%
% Generation of a two class k dimensional dataset A. Both classes
% are Gaussian distributed with identy matrix
www.eeworm.com/read/469416/6976334
m conffig.m
function fh=conffig(y, t)
%CONFFIG Display a confusion matrix.
%
% Description
% CONFFIG(Y, T) displays the confusion matrix and classification
% performance for the predictions mat{y} compared
www.eeworm.com/read/449504/7502297
m clustermap.m
function [out,out2]=clustermap(long,lat,dataset,clustnum,method,varargin)
% PURPOSE: This function links a map and a bar plot of the classification variable created by the kmeans method
%-----------
www.eeworm.com/read/299459/7850819
m andrerr.m
function [err,r,inx] = andrerr( model, distrib )
% ANDRERR Classification error of the Generalized Anderson's task.
%
% Synopsis:
% [err,r,inx] = andrerr( model, distrib )
%
% Description:
% This
www.eeworm.com/read/398324/7994108
m svc.m
function net = svc(arg, sv, w, bias)
% SVC
%
% Construct a support vector classification (SVC) network object.
%
% Examples:
%
% % default constructor (linear, hardmargin SVC with no suppo