有向无环图支持向量(DAG-SVMS)多类分类方法,是一种新的多类分类方法。该方法采用了最小超球体类包含作为层次分类依据。试验结果表明,采用该方法进行多类分类,跟已有的分类方法相比有更高的分类精度。
上传时间： 2016-03-19
上传用户：1109003457
This is SvmFu, a package for training and testing support vector machines (SVMs). It s written in C++. It uses templates. The advantage of templates is that the types of kernel values and data points can be varied to suit the problem.
标签： machines training package testing
上传时间： 2015-07-03
上传用户：zhengzg
多分类支持向量机实现方法的分析比较：一对一、一对多和DAG的对比，比较专业，
上传时间： 2015-08-13
上传用户：hoperingcong
用C语言实现了编译系统中的DAG算法。 处理的比较简单。
上传时间： 2014-01-09
上传用户：asddsd
Dag Erling http library source code
标签： library Erling source http
上传时间： 2013-12-05
上传用户：ecooo
New training algorithm for linear classification SVMs that can be much faster than SVMlight for large datasets. It also lets you direcly optimize multivariate performance measures like F1-Score, ROC-Area, and the Precision/Recall Break-Even Point.
标签： classification algorithm for training
上传时间： 2014-12-20
上传用户：stvnash
MSJ-06Ⅱ-A 美国UNION UNION FLAG 型式番号：SVMS-01 欧洲联盟AEU AEU ENACT 型式番号：AEU-09 AEU ENACT（量产型） 型式编号：AEU-09
上传时间： 2014-01-06
上传用户：nanxia
This example demonstrates how to use WEKA s SVMs classifier in Matlab.
标签： demonstrates classifier example Matlab
上传时间： 2013-12-18
上传用户：dbs012280
这个课程项目完成了给定DAG graph，找到所有拓扑排序并且输出。用到了指针和链表。对于学习C/C++和数据结构比较有帮助。
上传时间： 2017-06-14
上传用户：2467478207
In this paper we present a classifier called bi-density twin support vector machines (BDTWSVMs) for data classification. In the training stage, BDTWSVMs first compute the relative density degrees for all training points using the intra-class graph whose weights are determined by a local scaling heuristic strategy, then optimize a pair of nonparallel hyperplanes through two smaller sized support vector machine (SVM)-typed problems. In the prediction stage, BDTWSVMs assign to the class label depending on the kernel density degree-based distances from each test point to the two hyperplanes. BDTWSVMs not only inherit good properties from twin support vector machines (TWSVMs) but also give good description for data points. The experimental results on toy as well as publicly available datasets indicate that BDTWSVMs compare favorably with classical SVMs and TWSVMs in terms of generalization
标签： recognition Bi-density machines support pattern vector twin for
上传时间： 2019-06-09
上传用户：lyaiqing
