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1.
Learning Classifier System Ensembles With Rule-Sharing   总被引:2,自引:0,他引:2  
This paper presents an investigation into exploiting the population-based nature of learning classifier systems (LCSs) for their use within highly parallel systems. In particular, the use of simple payoff and accuracy-based LCSs within the ensemble machine approach is examined. Results indicate that inclusion of a rule migration mechanism inspired by parallel genetic algorithms is an effective way to improve learning speed in comparison to equivalent single systems. Presentation of a mechanism which exploits the underlying niche-based generalization mechanism of accuracy-based systems is then shown to further improve their performance, particularly, as task complexity increases. This is not found to be the case for payoff-based systems. Finally, considerably better than linear speedup is demonstrated with the accuracy-based systems on a version of the well-known Boolean logic benchmark task used throughout.  相似文献   

2.
A neural classifier with random thresholds is considered. Probabilistic analysis of functional characteristics depending on the classifier parameters is performed, and recommendations for their selection are made. The classifier structure optimization is proposed for input data distribution.  相似文献   

3.
随机谕言模型   总被引:2,自引:0,他引:2  
贾小英  李宝  刘亚敏 《软件学报》2012,23(1):140-151
介绍了可证明安全理论中的重要工具——随机谕言模型,包括随机谕言模型的起源、基本性质和方法、随机谕言模型中的代表方案、明文知晓性质、随机谕言的实例化、随机谕言不可实例化的性质和相关负面结论以及对弱化的随机谕言模型的研究.此外,比较了随机谕言模型和其他理想模型,简介了标准模型中的方案设计状况.  相似文献   

4.
Neural Processing Letters - We propose a multi-step training method for designing generalized linear classifiers. First, an initial multi-class linear classifier is found through regression. Then...  相似文献   

5.
师彦文  王宏杰 《计算机科学》2017,44(Z11):98-101
针对不平衡数据集的有效分类问题,提出一种结合代价敏感学习和随机森林算法的分类器。首先提出了一种新型不纯度度量,该度量不仅考虑了决策树的总代价,还考虑了同一节点对于不同样本的代价差异;其次,执行随机森林算法,对数据集作K次抽样,构建K个基础分类器;然后,基于提出的不纯度度量,通过分类回归树(CART)算法来构建决策树,从而形成决策树森林;最后,随机森林通过投票机制做出数据分类决策。在UCI数据库上进行实验,与传统随机森林和现有的代价敏感随机森林分类器相比,该分类器在分类精度、AUC面积和Kappa系数这3种性能度量上都具有良好的表现。  相似文献   

6.
Diversity among the members of a team of classifiers is deemed to be a key issue in classifier combination. However, measuring diversity is not straightforward because there is no generally accepted formal definition. We have found and studied ten statistics which can measure diversity among binary classifier outputs (correct or incorrect vote for the class label): four averaged pairwise measures (the Q statistic, the correlation, the disagreement and the double fault) and six non-pairwise measures (the entropy of the votes, the difficulty index, the Kohavi-Wolpert variance, the interrater agreement, the generalized diversity, and the coincident failure diversity). Four experiments have been designed to examine the relationship between the accuracy of the team and the measures of diversity, and among the measures themselves. Although there are proven connections between diversity and accuracy in some special cases, our results raise some doubts about the usefulness of diversity measures in building classifier ensembles in real-life pattern recognition problems.  相似文献   

7.
作为一种著名的特征抽取方法,Fisher线性鉴别分析的基本思想是选择使得Fisher准则函数达到最大值的向量(称为最优鉴别向量)作为最优投影方向,以便使得高维输入空间中的模式样本在该向量投影后,在类间散度达到最大的同时,类内散度最小。大间距线性分类器是寻找一个最优投影矢量(最优分隔超平面的法向量),它可使得投影后的两类样本之间的分类间距(Margin)最大。为了获得更佳的识别效果,结合Fisher线性鉴别分析和大间距分类器的优点,提出了一种新的线性投影分类算法——Fisher大间距线性分类器。该分类器的主要思想就是寻找最优投影矢量wbest(最优超平面的法向量),使得高维输入空间中的样本模式在wbest上投影后,在使类间间距达到最大的同时,使类内离散度尽可能地小。并从理论上讨论了与其他线性分类器的联系。在ORL人脸库和FERET人脸数据库上的实验结果表明,该线性投影分类算法的识别率优于其他分类器。  相似文献   

8.
Journal of Computer Science and Technology - We present new variants of Estimation of Distribution Algorithms (EDA) for large-scale continuous optimisation that extend and enhance a recently...  相似文献   

9.
One of the main problems in pattern recognition is obtaining the best set of features to represent the data. In recent years, several feature extraction algorithms have been proposed. However, due to the high degree of variability of the patterns, it is difficult to design a single representation that can capture the complex structure of the data. One possible solution to this problem is to use a multiple-classifier system (MCS) based on multiple feature representations. Unfortunately, still missing in the literature is a methodology for comparing and selecting feature extraction techniques based on the dissimilarity of the feature representations. In this paper, we propose a framework based on dissimilarity metrics and the intersection of errors, in order to analyze the relationships among feature representations. Each representation is used to train a classifier, and the results are compared by means of a dissimilarity metric. Then, with the aid of Multidimensional Scaling, visual representations are obtained of each of the dissimilarities and used as a guide to identify those that are either complementary or redundant. We applied the proposed framework to the problem of handwritten character and digit recognition. The analysis is followed by the use of an MCS built on the assumption that combining dissimilar feature representations can greatly improve the performance of the system. Experimental results demonstrate that a significant improvement in classification accuracy is achieved due to the complementary nature of the representations. Moreover, the proposed MCS obtained the best results to date for both the MNIST handwritten digit dataset and the Cursive Character Challenge (C-Cube) dataset.  相似文献   

10.
11.
在特征匹配问题中,匹配速度与精度常常难以同时保证。为了解决该问题,本文提出一种基于随机森林的特征匹配算法。结合SUSurE算法,在尺度空间下提取局部不变特征,构建训练样本集合,对随机森林进行离线训练建立分类模型。在实时匹配中,选取候选特征点对其进行实时分类,完成特征匹配,并与SIFT算法在不同尺度、旋转、视角方面等进行实验对比。结果表明,本文算法在具有良好的实时性情况下,仍有较高的光照适应性和匹配精度。  相似文献   

12.
线性支持向量机多类分类器几何构造方法   总被引:1,自引:0,他引:1       下载免费PDF全文
唐英  李应珍 《计算机工程》2012,38(4):152-154
针对支持向量机多类分类问题,根据样本点集凸包找寻模式类间隙,通过提取模式类间隙多边形中轴线构造多类分类边界。当基本支持向量机扩展为多类分类问题时,该方法克服了OAO和OAA等传统方法存在的决策盲区和类别不平衡等缺陷。基于仿真数据集的 实验结果表明,构造的分类边界在保证分类精度的同时,能够使分类空隙最大化,实现对线性可分多类数据的最优分类。  相似文献   

13.
《Automatica》1987,23(2):237-240
In a random environment, Jump Linear Quadratic control problems are studied. Random state discontinuities are included in the analysis and the corresponding optimal regulator is obtained. The introduction of stochastic notions of stabilizability and detectability gives a direct characterization of the asymptotic behaviour of the optimal system.  相似文献   

14.
机器学习算法为很多安全应用提供了良好的解决方案,然而机器学习算法本身却面临被敌手攻击的威胁。为分析敌手攻击对机器学习算法造成的影响,本文提出符合某些特定场合的敌手攻击模型,并在该模型下比较几种线性分类器的对抗性。最后在垃圾邮件过滤公开数据库上进行测试,实验结果表明,支持向量分类器具有相对较好的对抗性。  相似文献   

15.
一种基于局部随机子空间的分类集成算法   总被引:1,自引:0,他引:1  
分类器集成学习是当前机器学习研究领域的热点之一。然而,经典的采用完全随机的方法,对高维数据而言,难以保证子分类器的性能。 为此,文中提出一种基于局部随机子空间的分类集成算法,该算法首先采用特征选择方法得到一个有效的特征序列,进而将特征序列划分为几个区段并依据在各区段的采样比例进行随机采样,以此来改进子分类器性能和子分类器的多样性。在5个UCI数据集和5个基因数据集上进行实验,实验结果表明,文中方法优于单个分类器的分类性能,且在多数情况下优于经典的分类集成方法。  相似文献   

16.
We show that for arbitrary positive integers with probability the gcd of two linear combinations of these integers with rather small random integer coefficients coincides with This naturally leads to a probabilistic algorithm for computing the gcd of several integers, with probability via just one gcd of two numbers with about the same size as the initial data (namely the above linear combinations). This algorithm can be repeated to achieve any desired confidence level.  相似文献   

17.
支持在线学习的增量式极端随机森林分类器   总被引:3,自引:0,他引:3  
提出了一种增量式极端随机森林分类器(incremental extremely random forest,简称IERF),用于处理数据流,特别是小样本数据流的在线学习问题.IERF算法中新到达的样本将被存储到相应的叶节点,并通过Gini系数来确定是否对当前叶节点进行分裂扩展,在给定有限数量,甚至是少量样本的情况下,I...  相似文献   

18.
提出一种基于线性的朴素贝叶斯分类器知识库组织方法.该方法按照朴素贝叶斯分类算法对所有条件概率进行统一计算,最后把计算结果储存在以枚举类型为下标的线性表当中,以便于快捷查找条件概率并结合先验概率来预测未知类属的样本.该方法具有可扩展性.  相似文献   

19.
20.
分类器线性组合的有效性和最佳组合问题的研究   总被引:8,自引:0,他引:8  
通过多个分类器的组合来提升分类精度是机器学习领域主要研究内容,弱学习定理保证了这种研究的可行性.分类器的线性组合,也即加权投票,是最常用的组合方法,其中广泛使用的AdaBoost算法和Bagging算法就是采取的加权投票.分类器组合的有效性问题以及最佳组合问题均需要解决.在各单个分类器互不相关和分类器数量较多条件下,得到了分类器组合有效的组合系数选取条件以及最佳组合系数公式,给出了组合分类器的误差分析.结论表明,当各分类器分类错误率有统一的边界时,即使采取简单投票,也能确保组合分类器分类错误率随分类器个数增加而以指数级降低.在此基础上,仿照AdaBoost算法,提出了一些新的集成学习算法,特别是提出了直接面向组合分类器分类精度快速提升这一目标的集成学习算法,分析并指出了这种算法的合理性和科学性,它是对传统的以错误率最低为目标的分类器训练与选取方法的延伸和扩展.从另一个角度证明了AdaBoost算法中采用的组合不仅有效,而且在一定条件下等效于最佳组合.针对多分类问题,得到了与二分类问题类似的分类器组合理论与结论,包括组合有效条件、最佳组合、误差估计等.还对AdaBoost算法进行了一定的扩展.  相似文献   

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