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/149739/12352710
m averagec.m
%AVERAGEC Combining of linear classifiers by averaging coefficients
%
% W = AVERAGEC(V)
% W = V*AVERAGEC
%
% INPUT
% V A set of affine base classifiers.
%
% OUTPUT
% W Combined classifier.
%
%
www.eeworm.com/read/149739/12352714
m rbnc.m
%RBNC Radial basis function neural network classifier
%
% W = RBNC(A,UNITS)
%
% INPUT
% A Dataset
% UNITS Number of RBF units in hidden layer
%
% OUTPUT
% W Radial basis neural n
www.eeworm.com/read/149739/12353575
m costm.m
%COSTM Cost mapping, classification using costs
%
% Y = COSTM(X,C,LABLIST)
% W = COSTM([],C,LABLIST)
%
% DESCRIPTION
% Maps the classifier output X (assumed to be posterior probability
% estimate
www.eeworm.com/read/148901/12415753
cpp knn.cpp
//====
// knn.cpp
// - k nearest neighbours (the classic case-based classifier)
// - returns the most likely category of a target according to
// its k nearest neighbours whose categories are kn
www.eeworm.com/read/130491/14189775
readme
DBACL - digramic Bayesian classifier
PURPOSE
dbacl is a command line program which can be used to categorize
several types of text documents. Each document category is
constructed as a maximum ent
www.eeworm.com/read/128468/14295375
m pbayescln.m
function pbayescln(MI,SIGMA,Pk,background, linestyle)
% PBAYESCLN vizualizes Bayes classifier discriminant in 2D.
% pbayescln(MI,SIGMA,Pk,background, linestyle )
%
% This fucntion vizualizes discrimi
www.eeworm.com/read/128468/14295678
m fishdemo.m
function []=fishdemo(action,hfigure,varargin)
% FISHDEMO demo on algorithms which learn Fisher's classifer.
%
% FISHDEMO demonstrates use of algorithms finding the Fisher's
% classifier. The task is
www.eeworm.com/read/128193/14311413
m getsv.m
function sv = getsv(net)
% GETSV
%
% Accessor method returning the support vectors of a support vector
% classifier network.
%
% sv = getsv(net);
%
% File : @svc/getsv.m
%
% D
www.eeworm.com/read/128193/14311420
m getw.m
function w = getw(net)
% GETW
%
% Accessor method returning the weights of a support vector classifier network.
%
% w = getw(net);
%
% File : @svc/getw.m
%
% Date : Tuesd
www.eeworm.com/read/223114/14656509
m mahalclassifer.m
function [ClassRate] = MahalClassifer(train_pattern, train_label, test_pattern,test_label,a)
%%%%%%%%%%%%%%%%% this function is for mean nearest classifier
% a for mix mahal distance
% m for eachnu