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Monotonic decision tree for interval valued data 13

Monotonic decision tree for interval valued data

引用

13th International Conference on machine learning and Cybernetics, ICMLC 2014

作者： Zhu, Hong Zhai, Junhai Wang, Shanshan Wang, Xizhao Key Laboratory of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding071002 China

ISBN: (纸本)9783662456514

Traditional decision tree algorithms for interval valued data only can deal with non-ordinal classification problems. In this paper, we presented an algorithm to solve the ordinal classification problems, where both the condition attributes with interval values and the decision attributes meet the monotonic requirement. The algorithm uses the rank mutual information to select extended attributes, which guarantees that the outputted decision tree is monotonic. The proposed algorithm is illustrated by a numerical example, and a monotonically consistent decision tree is generated. The design of algorithm can provide some useful guidelines for extending real-vauled to interval-valued attributes in ordinal decision tree induction. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Decision trees

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Integrating local information-based link prediction algorithms with owa operator

Integrating local information-based link prediction algorith...

引用

3rd International Conference on Pattern Recognition Applications and Methods, ICPRAM 2014

作者： Liu, James N.K. He, Yu-Lin Hu, Yan-Xing Wang, Xi-Zhao Shiu, Simon C.K. Department of Computing Hong Kong Polytechnic University Kowloon Hong Kong Key Laboratory in Machine Learning and Computational Intelligence of Hebei Province College of Mathematics and Computer Science Hebei University Baoding 071002 China

ISBN: (纸本)9789897580185

The objective of link prediction for social network is to estimate the likelihood that a link exists between two nodes x and y. There are some well-known local information-based link prediction algorithms (LILPAs) which have been proposed to handle this essential and crucial problem in the social network analysis. However, they can not adequately consider the so-called local information: The degrees of x and y, the number of common neighbors of nodes x and y, and the degrees of common neighbors of x and y. In other words, not any LILPA takes into account all the local information simultaneously. This limits the performances of LILPAs to a certain degree and leads to the high variability of LILPAs. Thus, in order to make full use of all the local information and obtain a LILPA with highly-predicted capability, an ordered weighted averaging (OWA) operator based link prediction ensemble algorithm (LPEOWA) is proposed by integrating nine different LILPAs with aggregation weights which are determined with maximum entropy method. The final experimental results on benchmark social network datasets show that LPEOWA can obtain higher prediction accuracies which is measured by the area under the receiver operating characteristic curve (AUC) in comparison with nine individual LILPAs. Copyright © 2014 SCITEPRESS.

关键词： Maximum entropy methods

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Robust smooth one-class support vector machine

Robust smooth one-class support vector machine

引用

International Conference on Information Technology and Electronic Commerce

作者： Jin-Kou Hu Hong-Jie Xing Key Laboratory of Machine Learning and Computational Intelligence Hebei University Baoding Hebei Province China

ISBN: (纸本)9781479953004

In this paper, a novel one-class classification approach, namely, robust smooth one-class support vector machine (RSOCSVM) is proposed. The proposed method can efficiently enhance the anti-noise ability of the traditional one-class support vector machine (OCSVM). Utilizing the smooth technique, RSOCSVM reformulates the quadratic programming problem of OCSVM as an unstrained optimization format. Moreover, half-quadratic minimization is used to solve the obtained unstrained optimization problem. Experimental results on two synthetic data sets and nine benchmark data sets demonstrate that the proposed method is superior to the traditional OCSVM.

关键词： Optimization Support vector machines Robustness Accuracy Minimization Training Benchmark testing

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A maintenance algorithm of FDS based mathematical expression index

A maintenance algorithm of FDS based mathematical expression...

引用

International Conference on machine learning and Cybernetics (ICMLC)

作者： Song-Qiang Yang Xue-Dong Tian Hebei key laboratory of Machine Learning and Computational Intelligence Hebei University Baoding China

ISBN: (纸本)9781479942145

Mathematical expressions have complex two dimensions structure which could not be processed properly by traditional full-text retrieval method. It is necessary for us to research and develop special retrieval theory and technology including the indexing and matching methods of mathematical expressions which fully considers the characteristics of them. In this paper, a maintenance algorithm is designed for the mathematical expression index based on FDS which we given previously. Firstly, the existing achievements about mathematical expression recognition and retrieval are introduced and discussed. Then, the FDS is defined based on formula structural tree and the corresponding mathematical expression index is constructed. Finally, the index maintenance algorithms including the searching, inserting, and deleting operations of index items corresponding to the FDS based index are designed. The experimental result shows that the proposed method is helpful for the mathematical resources management and retrieval.

关键词： Maintenance engineering Indexes Abstracts Information management

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Ensemble online sequential extreme learning machine for large data set classification

Ensemble online sequential extreme learning machine for larg...

引用

IEEE International Conference on Systems, Man, and Cybernetics

作者： Junhai ZHAI Jinggeng WANG Xizhao WANG College of Mathematics and Computer Science Hebei University Key Laboratory of Machine Learning and Computational Intelligence of Hebei Province College of Mathematics and Computer Science Hebei University

ISBN: (纸本)9781479938414

Online sequential extreme learning machine (OS-ELM) proposed by Liang et al. employ sequential learning strategy to learn the target concept from the data. Compared with the original ELM, OS-ELM can learn data one-by-one or chunk-by-chunk with fixed or varying chunk size with almost same performance as ELM. While compared with other state-of-the-art sequential algorithms such as SGBP, RAN and GAP-RBF, OS-ELM has faster learning speed and better generalization ability. However, similar to ELM, OS-ELM also has instability in different trials of simulations. In addition, for large data sets, OS-ELM will not halt when there are training samples not be learned, this phenomenon results in long learning time. In order to deal with the problems, this paper proposes an algorithm named E-OS-ELM for integrating OS-ELM to classify large data sets. The experimental results show that the proposed method is effective and efficient;it can effectively overcome the drawbacks mentioned above.

关键词： Extreme learning machine Ensemble Sequential learning Large data set

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A Method of Mathematical Formula Detection in PDF Documents

A Method of Mathematical Formula Detection in PDF Documents

引用

2012 International Conference on Applied Informatics and Communication(ICAIC 2012)

作者： Na Jiao Xuedong Tian Xuesha Jia Bei Xue College of Mathematics and Computer Science Hebei University Key Laboratory of Machine Learning and Computational Intelligence Hebei University

With the wide application of PDF documents,how to detect the documents which contains mathematical formulas from the vast amount of documents is in great important meaning for formula location,identification and *** on the font analysis of 132 kinds of layouts come from journals and conference proceedings in different fields,the font and operator features of mathematical formulas in PDF documents are induced,14 kinds of fonts for mathematical formulas are summarized ***,PDF's character encoding way is analyzed and a mapping table for mathematical operators is ***,a method of rapid detection of mathematical formulas in PDF documents is designed using the features of fonts and operators in PDF *** experimental result shows the effectiveness of the method.

关键词： PDF documents Mathematical formula detection Font Operators

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Feature Extraction by Correntropy Based Average Neighborhood Margin Maximization

Feature Extraction by Correntropy Based Average Neighborhood...

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第26届中国控制与决策会议

作者： Lin-Na Ma Hong-Jie Xing Shun-Yan Hou Key Laboratory of Machine Learning and Computational Intelligence College of Mathematics and Computer ScienceHebei University College of Electronics and Information Engineering Hebei University

ISBN: (纸本)9781479937097

Average neighborhood margin maximization(ANMM) is a feature extraction method to make homogeneous points collect as near as possible and heterogeneous points disperse as far away as possible. To enhance the anti-noise ability of ANMM, correntropy based average neighborhood margin maximization(CANMM) is proposed in this paper. This method utilizes correntropy to substitute the Euclidean distance for measuring the similarity between the given data, and uses the maximum correntropy criterion to replace the maximum distance criterion, which makes CANMM more robust. The experimental results on three benchmark face databases validate the effectiveness of the proposed method.

关键词： Feature Extraction,Half-quadratic optimization,Correntropy,ANMM

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A mathematical formula retrieval method using structure sub-tree

A mathematical formula retrieval method using structure sub-...

引用

3rd International Conference on Materials Science and Information Technology, MSIT 2013

作者： Guan, Ming Jie Tian, Xue Dong Yang, Fang Yang, Song Qiang College of Mathematics and Computer Science Hebei University Baoding China Hebei key laboratory of Machine Learning and Computational Intelligence Hebei University China

ISBN: (纸本)9783037857700

It is quite inadequate in providing formula retrieval function by traditional retrieval techniques used in full-text information retrieval system. The main reason is that there are many difficulties to extract the keywords of the mathematical formulas. In this paper, a detailed analysis of the structural characteristics of mathematical formulas and existing index mechanism of mathematical formula searching engine is fulfilled. Then a full-text index (named SLIndex) of mathematical formulas with B+ tree structure is designed and implemented which extracts the structured logic sub-tree feature as keywords of formulas and employs inverted index. Finally, a formula search engine model based on SLIndex is implemented in Apache 2.0 web server. © (2013) Trans Tech Publications, Switzerland.

关键词： Search engines

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Audio retrieval based on Chinese keyword search in relational databases

Audio retrieval based on Chinese keyword search in relationa...

引用

3rd International Conference on Materials Science and Information Technology, MSIT 2013

作者： Zhu, Bo Yan Liu, Guang Zhu, Liang College of Art Hebei University Baoding Hebei 071002 China Key Laboratory of Machine Learning and Computational Intelligence School of Mathematics and Computer Science Hebei University Baoding Hebei 071002 China

ISBN: (纸本)9783037857700

In this paper, we propose a new method based on Chinese keyword search to select the WAV or MP3 files in audio post-production. First, we listen to each file and label it with Chinese characters, and then classify and store the files in a relational database system. Then, we use the techniques of Chinese keyword search to match query characters and the tuple characters quickly, and to compute similarities between the query and candidate tuples. For the characteristics of Chinese keyword search, we present a ranking strategy and an algorithm to refine the candidate tuples resulting from the first round matching, and finally get top-N results of audio files. The experimental results show that our method is efficient and effective. © (2013) Trans Tech Publications, Switzerland.

关键词： Relational database systems

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An indexing method of mathematical expression retrieval

An indexing method of mathematical expression retrieval

引用

International Conference on Computer Science and Network Technology (ICCSNT)

作者： Xuedong Tian Songqiang Yang Xinfu Li Fang Yang Hebei key laboratory of Machine Learning and Computational Intelligence Baoding China College of Mathematics & Computer Science Hebei University Baoding China

ISBN: (纸本)9781479905607

As the kernel component of scientific documents, mathematical expressions are becoming a new object of searching engines. Different from normal text, mathematical expressions are composed of various kinds of symbols arranged in nonlinear mode, which results in the limitations of traditional full-text information retrieval used for expression searching. In this paper, we discuss the existing search engine of mathematical expressions and introduce the two-dimensional characteristics of mathematical expressions firstly. Then, a data structure of expressing mathematical formulas is designed which contains not only the symbol code but also the mathematical information among symbols. Finally, the indexing algorithm of mathematical expressions is put forward on the basis of the expression data structure. The experimental result shows the effectiveness of the indexing method proposed in this paper.

关键词： Feature extraction Search engines Data mining Indexing Educational institutions Data structures

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