期刊文献+
共找到3篇文章
< 1 >
每页显示 20 50 100
一种基于聚类的核向量机参数C选择算法
1
作者 王奇安 陈兵 冯爱民 《小型微型计算机系统》 CSCD 北大核心 2011年第3期521-525,共5页
核向量机可以高效学习大样本数据集,却有泛化能力低的缺陷.针对已有参数C选择算法缺乏启发性以及选取困难的不足,本文在分析了核聚类算法和距离比较算法的基础之上,提出基于核聚类的相对距离比较方法,该算法利用核聚类算法在特征空间对... 核向量机可以高效学习大样本数据集,却有泛化能力低的缺陷.针对已有参数C选择算法缺乏启发性以及选取困难的不足,本文在分析了核聚类算法和距离比较算法的基础之上,提出基于核聚类的相对距离比较方法,该算法利用核聚类算法在特征空间对样本点进行聚类分簇,然后根据样本点到簇心相对距离的比值,得到参数C.本文在理论和实验两个方面,证明该算法有效地选择参数C,从而提高核支持向量机算法的泛化能力. 展开更多
关键词 核向量机 核聚类 惩罚因子C 选择算法 相对距离比较
在线阅读 下载PDF
正则稀疏化的多因子量化选股策略 被引量:8
2
作者 舒时克 李路 《计算机工程与应用》 CSCD 北大核心 2021年第1期110-117,共8页
针对高维度数据集特征之间的复杂性,而传统的L1惩罚项不满足Oracle性质的无偏性,将逻辑回归弹性网(LR-Elastic Net)中的L1惩罚项替换为SCAD(Smoothly Clipped Absolute Deviation)和MCP(Minimax Concave Penalty)惩罚项,分别构建了LR-S... 针对高维度数据集特征之间的复杂性,而传统的L1惩罚项不满足Oracle性质的无偏性,将逻辑回归弹性网(LR-Elastic Net)中的L1惩罚项替换为SCAD(Smoothly Clipped Absolute Deviation)和MCP(Minimax Concave Penalty)惩罚项,分别构建了LR-SCAD和LR-MCP模型,在保留稀疏性的同时满足了无偏性,并利用ADMM(Alternating Direction Method of Multipliers)算法进行求解。通过模拟实验发现,LR-Elastic Net模型能很好地处理特征存在相关性的小样本数据,而LR-SCAD和LR-MCP模型在特征存在相关性的大样本数据中表现较好;建立LR-Elastic Net、LR-SCAD和LR-MCP策略,并应用于沪深300指数成分股数据。回测结果显示,LR-SCAD和LR-MCP策略在股票相关性很强的数据中比LR-Elastic Net策略表现更好。 展开更多
关键词 弹性网(Elastic Net) SCAD MCP ADMM算法 逻辑回归 多因子选股
在线阅读 下载PDF
Immune based computer virus detection approaches 被引量:1
3
作者 TAN Ying ZHANG Pengtao 《智能系统学报》 CSCD 北大核心 2013年第1期80-94,共15页
The computer virus is considered one of the most horrifying threats to the security of computer systems worldwide.The rapid development of evasion techniques used in virus causes the signature based computer virus det... The computer virus is considered one of the most horrifying threats to the security of computer systems worldwide.The rapid development of evasion techniques used in virus causes the signature based computer virus detection techniques to be ineffective.Many novel computer virus detection approaches have been proposed in the past to cope with the ineffectiveness,mainly classified into three categories: static,dynamic and heuristics techniques.As the natural similarities between the biological immune system(BIS),computer security system(CSS),and the artificial immune system(AIS) were all developed as a new prototype in the community of anti-virus research.The immune mechanisms in the BIS provide the opportunities to construct computer virus detection models that are robust and adaptive with the ability to detect unseen viruses.In this paper,a variety of classic computer virus detection approaches were introduced and reviewed based on the background knowledge of the computer virus history.Next,a variety of immune based computer virus detection approaches were also discussed in detail.Promising experimental results suggest that the immune based computer virus detection approaches were able to detect new variants and unseen viruses at lower false positive rates,which have paved a new way for the anti-virus research. 展开更多
关键词 数据挖掘 计算机技术 发展现状 人工智能
在线阅读 下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部