代码搜索：classifiers
找到约 2,305 项符合「classifiers」的源代码
代码结果 2,305
www.eeworm.com/read/299984/7140770
m prex_plotc.m
%PREX_PLOTC PRTools example on the dataset scatter and classifier plot
help prex_plotc
n = prprogress;
prprogress off
echo on
% Generate Higleyman data
A = gendath([100 100]);
www.eeworm.com/read/460435/7250491
m disperror.m
%DISPERROR Display error matrix with information on classifiers and datasets
%
% DISPERROR(DATA,CLASSF,ERROR,STD,FID)
%
% INPUT
% DATA Cell array of M datasets or dataset names (strings)
% CLAS
www.eeworm.com/read/460435/7251248
m rsscc.m
%RSSCC Random subspace combining classifier
%
% W = RSSCC(A,CLASSF,NFEAT,NCLASSF)
%
% INPUT
% A Dataset
% CLASSF Untrained base classifier
% NFEAT Number of features for train
www.eeworm.com/read/460435/7251252
m prex_plotc.m
%PREX_PLOTC PRTools example on the dataset scatter and classifier plot
help prex_plotc
n = prprogress;
prprogress off
echo on
% Generate Higleyman data
A = gendath([100 100]);
www.eeworm.com/read/451547/7461921
m dd_ex2.m
% DD_EX2
%
% Show the performance of a whole list of classifiers on a simple
% artificial one-class problem.
% Copyright: D.M.J. Tax, D.M.J.Tax@prtools.org
% Faculty EWI, Delft University of Techno
www.eeworm.com/read/451308/7467543
java examplesconstructor.java
package ir.classifiers;
import java.util.*;
import ir.vsr.*;
/**
* Creates a list of Examples from data files
* Specializations handle various ways of storing
* examples.
*
* @author Ray Mooney
www.eeworm.com/read/450608/7480131
m disperror.m
%DISPERROR Display error matrix with information on classifiers and datasets
%
% DISPERROR(DATA,CLASSF,ERROR,STD,FID)
%
% INPUT
% DATA Cell array of M datasets or dataset names (strings)
% CLAS
www.eeworm.com/read/441245/7672698
m disperror.m
%DISPERROR Display error matrix with information on classifiers and datasets
%
% DISPERROR(DATA,CLASSF,ERROR,STD,FID)
%
% INPUT
% DATA Cell array of M datasets or dataset names (strings)
% CLAS
www.eeworm.com/read/441245/7673470
m rsscc.m
%RSSCC Random subspace combining classifier
%
% W = RSSCC(A,CLASSF,NFEAT,NCLASSF)
%
% INPUT
% A Dataset
% CLASSF Untrained base classifier
% NFEAT Number of features for train
www.eeworm.com/read/397111/8067168
m dd_ex2.m
% DD_EX2
%
% Show the performance of a whole list of classifiers
% Generate data:
nrx = 50;
X = gendatb([nrx nrx]);
% Give names to the features:
X = set(X,'featlab',['height';'width ']);
% Use now