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统计量复杂性估计及其在机器学习中的应用 被引量:2
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作者 胡政发 《自动化学报》 EI CSCD 北大核心 2008年第10期1332-1336,共5页
定义并估计了假设空间的统计量复杂性.据此可以找到一个基数性不超过假设空间的VC(Vapnik-Chervonenkis)维多项式级的线性经验泛函集,利用该线性经验泛函集可以构造以所需的任意精度逼近假设空间中的任一函数的学习算法.同时给出了随机... 定义并估计了假设空间的统计量复杂性.据此可以找到一个基数性不超过假设空间的VC(Vapnik-Chervonenkis)维多项式级的线性经验泛函集,利用该线性经验泛函集可以构造以所需的任意精度逼近假设空间中的任一函数的学习算法.同时给出了随机生成这些泛函的方法. 展开更多
关键词 统计量复杂性 L-范数 VC维 glivenko-cantelli
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广义经验分布函数及其性质 被引量:1
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作者 王礼萍 程希明 关忠 《哈尔滨师范大学自然科学学报》 CAS 1999年第1期13-17,共5页
本文将经验分布函数推广到更一般的形式,称为广义经验分布函数.虽然广义经验分布函数已不再具有用频率估计概率的性质,但作为未知总体分布函数的估计量,它仍具有许多良好的渐近性质.本文还讨论了它的小样本性质和Bootstra... 本文将经验分布函数推广到更一般的形式,称为广义经验分布函数.虽然广义经验分布函数已不再具有用频率估计概率的性质,但作为未知总体分布函数的估计量,它仍具有许多良好的渐近性质.本文还讨论了它的小样本性质和Bootstrap逼近的相合性. 展开更多
关键词 经验分布函数 次序统计量 经验过程 广义
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A Glivenko-Cantelli Theorem and Weak Convergence for Empirical Processes of Associated Sequences for Discrete Case
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作者 关忠 曲绍平 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 1995年第1期1-4,共4页
AGlivenko-CantelliTheoremandWeakConvergenceforEmpiricalProcessesofAssociatedSequencesforDiscreteCase¥(关忠)(曲绍... AGlivenko-CantelliTheoremandWeakConvergenceforEmpiricalProcessesofAssociatedSequencesforDiscreteCase¥(关忠)(曲绍平)GUANZhong;QUSha... 展开更多
关键词 ss:glivenko-cantelli THEOREM ASSOCIATED sequence COVARIANCE structure positively DEPENDENCE
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Probabilistic, Statistical and Algorithmic Aspects of the Similarity of Texts and Application to Gospels Comparison
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作者 Soumaila Dembele Gane Samb Lo 《Journal of Data Analysis and Information Processing》 2015年第4期112-127,共16页
The fundamental problem of similarity studies, in the frame of data-mining, is to examine and detect similar items in articles, papers, and books with huge sizes. In this paper, we are interested in the probabilistic,... The fundamental problem of similarity studies, in the frame of data-mining, is to examine and detect similar items in articles, papers, and books with huge sizes. In this paper, we are interested in the probabilistic, and the statistical and the algorithmic aspects in studies of texts. We will be using the approach of k-shinglings, a k-shingling being defined as a sequence of k consecutive characters that are extracted from a text (k ≥ 1). The main stake in this field is to find accurate and quick algorithms to compute the similarity in short times. This will be achieved in using approximation methods. The first approximation method is statistical and, is based on the theorem of Glivenko-Cantelli. The second is the banding technique. And the third concerns a modification of the algorithm proposed by Rajaraman et al. ([1]), denoted here as (RUM). The Jaccard index is the one being used in this paper. We finally illustrate these results of the paper on the four Gospels. The results are very conclusive. 展开更多
关键词 SIMILARITY Web MINING Jaccard SIMILARITY RU Algorithm Minhashing Data MINING Shingling Bible’s GOSPELS glivenko-cantelli EXPECTED SIMILARITY STATISTICAL Estimation
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