OCSVM集成模型解决支持向量机的大规模训练问题

该文针对集成方法实现支持向量机大规模训练的相关问题进行了深入研究,提出了一种称为"DD-Boosting"的成员分类器产生算法,能够在大规模数据集情况下利用类似Boosting技术产生稳定、高泛化性能的成员分类器。在此基础上,推导出基于OCSVM的分类器集成模型,实验仿真表明,该集成模型能够获得比主投票方法更好的泛化性能,且通过调整正则参数避免了训练过拟合问题。     

Network traffic classification based on ensemble learning and co-training

Classification of network traffic is the essential step for many network researches. However,with the rapid evolution of Internet applications the effectiveness of the port-based or payload-based identifi-cation approaches has been greatly diminished in recent years. And many researchers begin to turn their attentions to an alternative machine learning based method. This paper presents a novel machine learning-based classification model,which combines ensemble learning paradigm with co-training tech-niques. Compared to previous approaches,most of which only employed single classifier,multiple clas-sifiers and semi-supervised learning are applied in our method and it mainly helps to overcome three shortcomings:limited flow accuracy rate,weak adaptability and huge demand of labeled training set. In this paper,statistical characteristics of IP flows are extracted from the packet level traces to establish the feature set,then the classification model is created and tested and the empirical results prove its feasibility and effectiveness.     

一种多分类器集成的手写体汉字识别方法

多分类器集成是手写体汉字识别领域的新方向。本文提出的多分类器集成方法通过改进的欧氏距离分类器将待识别汉字分类到某个粗分结果集中,然后根据粗分结果集选择1-N(one-against-rest)的SVM分类器对待识别汉字进行细分,最后用贝叶斯集成两级分类器。实验对国标一级汉字中的1034个手写汉字进行识别,证明了方案的有效性。     

基于改进Multi-Agent系统的基因表达数据的分析与研究

通过介绍改进的多代理系统在分析基因表达数据中的应用,揭示了运用普通分类器找出有效的分类基因,而且这些普通分类器在研究基因表达数据库时可被代理使用.这样就可得到一个具有大量基因特征的小子集,并且用它可以帮助辨认病人的临床状况和特征.实验表明代理通过改进和相互协作可改进其性能,并通过两个著名的基因表达问题来展示项目的研究成果,而且使得量度的准确性在维数增加时变得不很敏感.     

最小海明距离分类器的字符识别方法研究

应用最小海明距离(Hamming Distance,缩写HD)分类器,研制了一种新型的基于最小海明分类器的字符识别方法。讨论了该字符识别方法实现的技术路线,较好解决了理论的工程化应用问题,对500帧连续图像的时间字符进行实验,时间字符识别准确率为99.8%,达到了字符比较准确识别的目的。     

集成学习算法在不平衡分类中的应用研究

提出一种基于训练集分解的不平衡分类算法,该算法使用能输出后验概率的支持向量机作为分类器,使用基于测度层次信息源合并规则实现分类器的集成.在4个不同领域的不平衡数据集上的仿真实验表明:该算法有效提高分类器对正类样本的正确率,同时尽量减少对负类样本的误判.实验结果验证集成学习算法处理不平衡分类问题的有效性.     

利用地统计分析及GIS技术实现流域面雨量预报

根据地统计学及地理信息系统(GIS)的空间建模原理,采用工业标准的、开放的、统一的ArcObjects嵌入式组件开发方法,利用多模数值预报,研制并构建精细化的流域面雨量集合预报模型及雨涝区划单元定量降水应用组件,将其动态、无缝地嵌入到GIS应用系统中,自动生成子流域及雨涝区划面雨量预报指导产品.     

在癌症分类中基于PPS抽样的集成神经网络算法

针对样本重组的有效性和合理性问题,将PPS抽样技术引入样本重构,提出了基于PPS抽样的集成神经网络算法,以提高个体神经网络的准确性与差异度,并实现动态选择个体神经网络的神经网络集成新方法.最后在结肠癌数据集上进行实验,实验结果表明,该方法与采用多个互相合作互相竞争的个体神经网络集成方法相当,但计算量更小,所用运算时间更少,效率更高.     

基于子空间集成学习的3维人体运动识别

如何对3维运动数据进行自动识别,是提高数据利用效率和进行计算机动画创作的前提。为了有效地识别运动数据,需要把运动数据投影到非线性流型低维子空间中,先识别出运动的内在结构,然后对运动的各个关节点分别进行学习,最后基于集成学习的方法产生强的隐马尔可夫学习器,以便能够对一些常见的运动类型进行自动识别。实验结果表明,这种基于子空间集成的人体运动识别方法较传统方法的检索精度、检索速度均有较大提高。     

Molecular simulation of phase coexistence: Finite-size effects and determination of critical parameters for two- and three-dimensional Lennard-Jones fluids

Abstact The subject of this paper is the investigation of finite-size effects and the determination of critical parameters for a class of truncated Lennard-Jones potentials. Despite significant recent progress in our ability to model phase equilibria in multicomponent mixtures from direct molecular simulations, the accurate determination of critical parameters remains a difficult problem. Gibbs ensemble Monte Carlo simulations with systems of controlled linear system size are used to obtain the phase behavior in the near-critical region for two- and three dimensional Lennard-Jones fluids with reduced cutoff radii of 3, 3.5, and 5. For the two-dimensional systems, crossover of the effective exponent for the width of the coexistence curve from mean field ( = 1/2 in the immediate vicinity of the critical point to Ising-like (= 1/8) farther away is observed. Critical parameters determined by fitting the data that follow Ising-like behavior are in good agreement with literature values obtained with finite-size scaling methods. For the three-dimensional systems, no crossover to mean field-type behavior was apparent. Extrapolated results for the critical parameters are consistent with literature estimates for similar fluids. For both two- and three-dimensional fluids, system size effects on the coexistence curves away from the critical point are small, normally within simulation statistical uncertainties.Invited paper presented at the Twelfth Symposium on Thermophysical Properties, June 19–24, 1994, Boulder. Colorado, U.S.A.