MIMLmiSVM
所属分类：matlab编程
开发工具：matlab
文件大小：1282KB
下载次数：46
上传日期：2014-01-15 15:08:47
上 传 者：
wyntabby
说明： matlab编写的多示例多标记分类程序，采用miSVM算法，svm做分类器，其中附有各个调用函数，和作为例子的数据和主程序，可以运行，可以多多示例多标记样本进行分类。
(matlab prepared multi-instance multi-label classification procedures, using miSVM algorithm, svm do classifier, which function with each call, and as an example of the data and the main program, you can run, you can sample a lot of examples of multi-label classification.)
文件列表:
MIMLmiSVM\libsvm-mat-2.86-1.zip (80739, 2008-06-25)
MIMLmiSVM\miml data.mat (631869, 2006-12-05)
MIMLmiSVM\MIMLmiSVM_test.m (788, 2009-10-18)
MIMLmiSVM\MIMLmiSVM_train.m (667, 2009-10-18)
MIMLmiSVM\miSVM_test.m (1222, 2009-03-24)
MIMLmiSVM\miSVM_train.m (1967, 2009-10-18)
MIMLmiSVM\sample_data.mat (609285, 2011-10-15)
MIMLmiSVM (0, 2013-12-17)
% This is a simple example on how to use the MIMLmiSVM package
% The libsvm toolbox [1] is included in this package and should be unzipped before running the algorithms
% [1] Chih-Chung Chang and Chih-Jen Lin, LIBSVM : a library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2:27:1--27:27, 2011. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
% Load the MIML data
load('sample_data.mat');
% set the parameters, para.svm is the parameter string of SVM just the same with that of libsvm
para.svm = '-t 2 -g 1 -b 1';
% Train the classifers:
classifiers = MIMLmiSVM_train(train_bags,train_target,para);
% Test:
[outputs,predictions] = MIMLmiSVM_test(test_bags,test_target,classifiers);
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