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/460435/7251196
m fisherc.m
%FISHERC Fisher's Least Square Linear Classifier
%
% W = FISHERC(A)
%
% INPUT
% A Dataset
%
% OUTPUT
% W Fisher's linear classifier
%
% DESCRIPTION
% Finds the linear discriminant functio
www.eeworm.com/read/460435/7251253
m testcost.m
function e = testcost(x,w,C,lablist)
%TESTCOST compute the error using the cost matrix C
%
% E = TESTCOST(A,W,C,LABLIST)
% E = TESTCOST(A*W,C,LABLIST)
% E = A*W*TESTCOST([],C,LABLIST)
%
%
www.eeworm.com/read/455344/7373041
cpp example.cpp
// Example.cpp : Defines the entry point for the console application.
//
#include "../BoostedCommittee.h"
#include "stdafx.h"
int main(int argc, char* argv[])
{
double Sample[25] = { 192
www.eeworm.com/read/454193/7397162
cpp example.cpp
// Example.cpp : Defines the entry point for the console application.
//
#include "../BoostedCommittee.h"
#include "stdafx.h"
int main(int argc, char* argv[])
{
double Sample[25] = { 192
www.eeworm.com/read/451547/7461894
m isocc.m
%ISOCC True for one-class classifiers
%
% isocc(w) returns true if the classifier w is a one-class classifier,
% outputting only classes 'target' and/or 'outlier' and having a
% structure with thr
www.eeworm.com/read/451547/7461905
m dd_roc.m
function [e, thr] = dd_roc(a,w)
%DD_ROC Receiver Operating Characteristic curve
%
% E = DD_ROC(A,W)
% E = DD_ROC(A*W)
% E = A*W*DD_ROC
%
% Find for a (data description) method W
www.eeworm.com/read/451547/7461937
m dd_ex3.m
% DD_EX3
%
% Show the use of the ksvdd: the support vector data description using
% several different kernels.
%
% To be honest, the SVDD is the most useful using the RBF kernel. In
% most case
www.eeworm.com/read/451547/7461940
m plotroc_update.m
function plotroc_update(w,a)
% PLOTROC_UPDATE(W,A)
%
% Auxiliary function containing the callbacks for the plotroc.m.
%
% See also: plotroc
% Copyright: D.M.J. Tax, D.M.J.Tax@prtools.org
% Faculty EW
www.eeworm.com/read/451547/7461942
m consistent_occ.m
function [w1,optval] = consistent_occ(x,w,fracrej,range,nrbags,varargin)
%CONSISTENT_OCC
%
% W = CONSISTENT_OCC(X,W,FRACREJ,RANGE,NRBAGS)
%
% Optimize the hyperparameters of method W. W should con
www.eeworm.com/read/451547/7461978
m dd_roc_old.m
function [e,thr] = dd_roc_old(w,a,b,frac_rej)
% e = dd_roc_old(W,A,B,frac_rej)
%
% Find for a (data description) method W (trained with A) the
% Receiver Operating Characteristic curve over datase