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共 52 条记录，以下是11-20 订阅

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The condensed fuzzy k-nearest neighbor rule based on sample fuzzy entropy

The condensed fuzzy k-nearest neighbor rule based on sample ...

引用

2011 International Conference on machine learning and Cybernetics, ICMLC 2011

作者： Zhai, Jun-Hai Li, Na Zhai, Meng-Yao Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China

ISBN: (纸本)9781457703065

The fuzzy k-nearest neighbor (F-KNN) algorithm was originally developed by Keller in 1985, which generalized the k-nearest neighbor (KNN) algorithm and could overcome the drawback of KNN in which all of instances were considered equally important. However, the F-KNN algorithm still suffers from the problem of large memory requirement same as the KNN. In order to deal with the problem, this paper proposes the condensed fuzzy k-nearest neighbor rule (CFKNN) which selects the important instances based on sample fuzzy entropy. The experimental results show that our proposed method is feasible and effective. © 2011 IEEE.

关键词： Motion compensation

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The application of decision tree in Chinese email classification

The application of decision tree in Chinese email classifica...

引用

International Conference on machine learning and Cybernetics

作者： Chen, Hao Zhan, Yan Li, Yan Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China

ISBN: (纸本)9781424465262

Email is a kind of semi-structured document, some important attributes are contained in its structure, and especially using spam-specific features could improve the email classification results. In this paper, we apply decision tree data mining technique to dig out the potential association rules among these attributes of email, and then to identify unknown email's category based on these rules. According to the experiment of applying numerous Chinese emails to our email classifier, the efficiency of our method is not lower than that of other existing methods of checking whole email content text. Meanwhile our method can reduce the cost of computation and consumption of system resources. © 2010 IEEE.

关键词： Association rules

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Data extraction based on index path in web

Data extraction based on index path in web

引用

2nd International Workshop on Education Technology and computer Science, ETCS 2010

作者： Gao, Ya Yuan, Fang Zhang, Ming Key Lab. in Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University BaodingHebei China

ISBN: (纸本)9780769539874

Data extraction in Web is to obtain the desired information to users in Web pages. For a more accurately valuable data extraction, this paper proposes a new method called data extraction based on index path in Web (DEIP). This approach establishes the index path for each text node using XML DOM;defines the prefix of data-rich by keywords in the index path;generate extraction rule and obtain a wrapper according. The wrapper can extract data automatically in the same domain from a Website. It does relevant to the continuity, the structural similarity, and the location relations of the useful information in Web pages, but not the HTML tag, Experiments indicate that this method is efficient in the recall and the precision of data extraction. © 2010 IEEE.

关键词： XML

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A fast support vector machine classification algorithm based on Karush-Kuhn-Tucker conditions 1

引用

12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2009

作者： Zhang, Ying Wang, Xizhao Zhai, Junhai Key Lab. for Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China

ISBN: (数字)9783642106460

ISBN: (纸本)3642106455

Although SVM have shown potential and promising performance in classification, they have been limited by speed particularly when the training data set is large. In this paper, we propose an algorithm called the fast SVM classification algorithm based on Karush-Kuhn-Tucker (KKT) conditions. In this algorithm, we remove points that are independent of support vectors firstly in the training process, and then decompose the remaining points into blocks to accelerate the next training. From the theoretical analysis, this algorithm can remarkably reduce the computation complexity and accelerate SVM training. And experiments on both artificial and real datasets demonstrate the efficiency of this algorithm. © 2009 Springer-Verlag Berlin Heidelberg.

关键词： Support vector machines

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A rank reduced matrix method in extreme learning machine

A rank reduced matrix method in extreme learning machine

引用

9th International Symposium on Neural Networks, ISNN 2012

作者： Lu, Shuxia Zhang, Guiqiang Wang, Xizhao Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding Hebei China

ISBN: (纸本)9783642313455

Extreme learning machine (ELM) is a learning algorithm for single-hidden layer feedforward neural networks (SLFNs) which randomly chooses hidden nodes and analytically determines the output weights of SLFNs. but when dealing with large datasets, we need more hidden nodes to enhance training and testing accuracy, in this case, this algorithm can't achieve high speed any more, sometimes its training can't be executed because the bias matrix is out of memory. We focus on this issue and use the Rank Reduced Matrix (MMR) method to calculate the hidden layer output matrix, the result showed this method can not only reach much higher speed but also better improve the generalization performance whenever the number of hidden nodes is large or not. © 2012 Springer-Verlag.

关键词： Singular value decomposition

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Case-based multi-task pathfinding algorithm

Case-based multi-task pathfinding algorithm

引用

2012 International Conference on machine learning and Cybernetics, ICMLC 2012

作者： Li, Yan Su, Lan-Ming He, Qiang Key Lab. in Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 Hebei Province China

ISBN: (纸本)9781467314855

Pathfinding is an important task in computer games, where the algorithm efficiency is the key issue. In this paper, we introduce case-based reasoning method in the process of A* algorithm in multi-task pathfinding. Firstly, we save some typical paths as cases. When a new task is coming, it no longer uses A* to find a path from scratch, but firstly computes the similarity of the new task and the stored cases to decide whether to go along the previous found paths or not. A solution to the new task will be obtained after adapting to the found similar case(s). Obviously, this memory-based pathfinding can reduce the search time at the cost of using more memory to store found paths as cases. Through experimental results, it is demonstrated that, as the number of stored paths is increasing, fewer nodes are needed to be searched during the pathfinding process. © 2012 IEEE.

关键词： Case based reasoning

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Reductions in inconsistent decision systems based on dominance relations

Reductions in inconsistent decision systems based on dominan...

引用

International Conference on machine learning and Cybernetics

作者： Li, Yan Sun, Na-Xin Zhao, Jin Key Lab. In Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 Hebei Province China

ISBN: (纸本)9781424465262

By incorporating domination principle in inconsistent decision systems based on dominance relations, we define the concept of distribution function for a decision system to directly reflect the inconsistent degree of this system. A new type of distribution reduction and maximum distribution reduction are correspondingly introduced. The relationships between these two reductions are discussed, and their judgment theorems are given. In addition, this article also discusses the relations of several existing reductions, including compatible reduction, absolute reduction, and the proposed distribution reduction and maximum distribution reduction. © 2010 IEEE.

关键词： Distribution functions

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Chinese functional chunk identification based on part of speech

Chinese functional chunk identification based on part of spe...

引用

International Conference on Communication Systems and Network Technologies, CSNT 2012

作者： Wang, Cheng-Yan Li, Xin-Fu Tian, Xue-Dong College of Mathematics and Computer Science Hebei University Baoding China Key Lab. in Machine Learning and Computational Intelligence of Hebei Province China

ISBN: (纸本)9780769546926

Chinese functional chunk describes the basic skeleton of the Chinese sentences. It is the important bridge for joining syntax and semantic description, and the Chinese functional chunk identification plays a key role in the field of natural language processing. Identifying the functional chunk is mostly based on methods of rules which come from the syntactic analysis. In this paper, the functional chunk is mainly identified according to the effect of the part of speech in the syntactic analysis. The experimental results show the proposed method works well on the functional chunk identification. © 2012 IEEE.

关键词： Semantics

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PSO-based method for learning similarity measure of nominal features

PSO-based method for learning similarity measure of nominal ...

引用

International Conference on machine learning and Cybernetics

作者： Li, Yan Zhang, Xiu-Li Key Lab. in Machine Learning and Computational Intelligence Faculty of Mathematics and Computer Science Hebei University Baoding 071002 Hebei Province China

ISBN: (纸本)9781424465262

This paper presents a PSO-based method for learning similarity measure of nominal features for case based reasoning classifiers (i.e. CBR classifiers). The symbolic features considered here takes completely unordered values. It has been indicated in [3] that in specific classification task, the similarities between these nominal feature values can not be simply considered as either 0 or 1. A GA-based approach has been developed for learning similarity measure of such feature values. However, when the number of features and feature values become larger, the GA-based algorithm's convergence speed obviously slows down, and the accuracy of classification may be also affected. To address this problem, we propose a PSO-based algorithm for learning similarity measure of nominal features and further describe feature importance through the learned similarity measure. The experimental results show that, using the proposed PSO-based algorithm, the convergence speed is much faster than that of GA-based algorithm and the accuracy is also improved. In addition, we also explain that the feature importance defined through the learned similarities is essentially consistent with that in rough sets, and an illustrative example is finally provided. © 2010 IEEE.

关键词： Particle swarm optimization (PSO)

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A survey of the initialization of centers and widths in radial basis function network for classification

A survey of the initialization of centers and widths in radi...

引用

2011 International Conference on machine learning and Cybernetics, ICMLC 2011

作者： Dong, Chun-Ru Chan, Patrick P.K. Ng, Wing W.Y. Yeung, Daniel S. Machine Learning and Cybernetics Research Center School of Computer Science and Engineering South China University of Technology Guangzhou 510006 China Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China

ISBN: (纸本)9781457703065

The radial basis function network (RBFN) has been widely used in various fields such as function regression, pattern recognition, and error detection, etc. However, the structural parameters of RBFN including the number of hidden units, centers vectors, and widths (variances) are one of the most importent issues when training a RBFN, which greatly affect the performance of RBFN. So, the objective of this paper is to construct an elementary survey about this problem. Firstly, the fundamental knowledge and notations of RBFN is introduced. Secondly, we summarize most existing network structure initialization methods for RBFN and categorize them into four goups. Then some typical appraoches for each category are introduced and discussed. The disadvantages and virtues for parts of methods are also introduced. Finally, the paper is concluded with a discussion of current difficulties and possible future directions about RBFN architecture selection. © 2011 IEEE.

关键词： Radial basis function networks

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