检索结果-内蒙古大学图书馆

2009 International Conference on machine learning and Cybernetics(2009机器学习与控制论国际会议)

作者： XI-ZHAO WANG HUI-QIN ZHAO SHUAI WANG Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Scie College of Mathematics and Computer Science Hebei University Baoding 071002 China

This paper is to discuss the reduction of computation complexity in decision tree generation for the numerical-valued attributes. The proposed method is based on the partition impurity. The partition impurity minimization is used to select the expanded attribute for generation the sub-node during the tree growth. After inducing the unstable cut-points of numerical-attributes, it is analytically proved that the partition impurity minimization can always be obtained at the unstable cut-points. It implies that the computation on stable cut-points may not be considered during the tree growth. Since the stable cut-points are far more than unstable cut-points, the experimental results show that the proposed method can reduce the computational complexity greatly.

关键词： Numerical-valued attributes decision trees Gini Indez Information entropy Partition impurity Unstable cut-point

来源：评论

学校读者我要写书评

暂无评论

RESEARCH ON CHINESE LOANWORDS CLASSIFICATION BASED ON FUZZY SET TECHNOLOGY

RESEARCH ON CHINESE LOANWORDS CLASSIFICATION BASED ON FUZZY ...

引用

2009 International Conference on machine learning and Cybernetics(2009机器学习与控制论国际会议)

作者： YAN-JIE LI ZHI-PING DIAO JUN-FEN CHEN College of Chinese Literature Hebei University Baoding 071002 Hebei China Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Scie

Classification is necessary and basic to scientific research. The Chinese loanword has always been a hot spot of studies on Chinese linguistics, however the range of it remained unsettled. The paper will introduce fuzzy set technology into the discriminant process of Chinese loanwords to compose a reliable and efficient classifier. Simulations verify the efficiency and feasibility.

关键词： Classification fuzzy set Membership function Chinese Loanwords Similarity

来源：评论

学校读者我要写书评

暂无评论

Selection of deep web database based on query relevance

引用

Journal of Information and computational Science 2009年第3期6卷 1113-1120页

作者： Yuan, Fang Fan, Jingchuan Liu, Shuang Zhang, Ming College of Mathematics and Computer Science Hebei University Hebei Baoding 071002 China Key Lab. in Machine Learning and Computational Intelligence of Hebei Province Hebei Baoding 071002 China College of Quality Technology Supervision Hebei University Hebei Baoding 071000 China

During recent years, there are more and more high-quality information in the Web database. Thus, it is becoming more and more important to find the most relevant Web database to user's query. In this paper, we propose a method to calculate the relevance of Web database with respect to user's query. The method submits frequent query to Web database, classifies the obtained results from the Web database by their characteristic, and calculates the relevance between the query and each type of obtained results together with the proportion of each type of the obtained result occupying all the results from all Web database. Meanwhile, the relevance between the query and the Web database is obtained through the weighted sum of the foresaid relevance and proportion. Experimental results on several actual Web databases demonstrate the effectiveness of the proposed method in evaluating the Web database's supporting power with specific queries. 1548-7741/ Copyright © 2009 Binary Information Press.

关键词： Query languages

来源：评论

学校读者我要写书评

暂无评论

MULTI-CLASS FUZZY SUPPORT VECTOR machine BASED ON DISMISSING MARGIN

MULTI-CLASS FUZZY SUPPORT VECTOR MACHINE BASED ON DISMISSING...

引用

2009 International Conference on machine learning and Cybernetics(2009机器学习与控制论国际会议)

作者： WEI-YUN YAN QIANG HE Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Scie Department of Mathematics Harbin Institute of Technology Harbin 150001 P.R.China

A new method, multi-class fuzzy support vector machine of dismissing margin (DMFSVM) based on class-center, is proposed aiming at the outliers and noises which appear in the large quantity samples. Compared with traditional SVM, this new method eliminates the sensibility of optimal separating hyperplane. It weeds out some sample points which may not be support vectors. And this will be able to decrease the corresponding optimization problem dimension, reduce the memory and the amount of computation, but increase the training speed. At the same time, the new algorithm adopts fuzzy membership function of decreasing Semi-Cauchy type. The advantages are through regulating parameters of fuzzy factor suitably according to the specific circumstances to make the fuzzy factor of isolated points smaller and the fuzzy factor of support vectors larger relatively. So this method can fit the characteristics of fuzzy classification well.

关键词： Fuzzy support vector machine Multi-class classification Mazimal margin of class-center The method of dismissing margin

来源：评论

学校读者我要写书评

暂无评论

SOME PROPERTIES OF OPERATIONS ON TYPE-2 FUZZY SETS

SOME PROPERTIES OF OPERATIONS ON TYPE-2 FUZZY SETS

引用

2008 International Conference on machine learning and Cybernetics(2008机器学习与控制论国际会议)

作者： SHUO WANG SHU-MING WANG YING LIU Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China

In this study, we study set operations on type-2 fuzzy sets. We first discuss join and meet operations of membership grades of type-2 fuzzy sets under left continuous t-norms and derive distributive law of type-2 fuzzy sets. Then, some properties on compositions of fuzzy relations is discussed. We derived that the distributive laws under union and composition of type-2 fuzzy relations is valid. An example shows the failure of distributive laws under intersection and composition.

关键词： Composition Fuzzy relation Operation Type-2 fuzzy set Triangular norm

来源：评论

学校读者我要写书评

暂无评论

A NEW ALGORITHM FOR SOLVING CONVEX HULL PROBLEM AND ITS APPLICATION TO FEATURE SELECTION

A NEW ALGORITHM FOR SOLVING CONVEX HULL PROBLEM AND ITS APPL...

引用

2008 International Conference on machine learning and Cybernetics(2008机器学习与控制论国际会议)

作者： FENG GUO XI-ZHAO WANG YAN LI Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 Hebei China

A new method to solve the convex hull problem in n-dimensional spaces is proposed in this paper. At each step, a new point is added into the convex hull if the point is judged to be out of the current convex hull by a linear programming model. For the linear separable classification problem, if an instance is regarded as a point of the instances space, the overlap does not still occur between the convex hulls of different classes after a feature is deleted, then we can delete that feature. Repeat this process, an algorithm for feature selection is given. Experimental results show the effectiveness of the algorithm.

关键词： Convez Hull Linear Programming Problem Feature Selection

来源：评论

学校读者我要写书评

暂无评论

NRMCS: NOISE REMOVING BASED ON THE MCS

NRMCS: NOISE REMOVING BASED ON THE MCS

引用

2008 International Conference on machine learning and Cybernetics(2008机器学习与控制论国际会议)

作者： XI-ZHAO WANG BO WU YU-LIN HE XIANG-HAO PEI Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 Hebei China

MCS (Minimal Consistent Set) is one of the classical algorithms for minimal consistent subset selection problem. However, when noisy samples are present classification accuracy can suffer. In addition, noise affect the size of minimal consistent set. Therefore, removing noise is an important issue before sample selection. In this paper, an improvement approach based on MCS to select the representative samples is proposed. Compared with other algorithms which remove the noise by Wilson Editing in advance for the representative samples selection, this algorithm performs the processes of noise removing and samples selection simultaneously. According to this method, most noise can be deleted and the most representative samples can be identified and retained. The experiments show that the proposed method can greatly remove the redundant samples and noise as well as increase the accuracy of solutions when it is used for classification tasks.

关键词： MCS Sample Selection ICF Representative Subset Noise Wilson Editing

来源：评论

学校读者我要写书评

暂无评论

AN INSTANCE SELECTION ALGORITHM BASED ON CONTRIBUTION

AN INSTANCE SELECTION ALGORITHM BASED ON CONTRIBUTION

引用

2008 International Conference on machine learning and Cybernetics(2008机器学习与控制论国际会议)

作者： XI-ZHAO WANG NING ZHANG TAO XIAO Key Lab.for Machine Learning and Computational Intelligence College of Mathematics and Computer Sci College of Science Agricultural University of Hebei Baoding 071002 China

This paper presents an approach to instance selection for the nearest neighbor rule which aims to obtain a condensed set with high condensing rate and prediction accuracy. By making an improvement on MCS algorithm and allowing certain error rate on the training set, a condensed set with high condensing rate and satisfying prediction accuracy is obtained. The condensed set is order-independent of the training instances and insensitive to noise. Comparative experiments have been conducted on real data sets, and the results show its superiority to MCS and FCNN in terms of condensing rate and prediction accuracy.

关键词： Instance selection nearest neighbor rule condensed set MCS FCNN

来源：评论

学校读者我要写书评

暂无评论

FUZZY DECISION TREE BASED ON THE IMPORTANT DEGREE OF FUZZY ATTRIBUTE

FUZZY DECISION TREE BASED ON THE IMPORTANT DEGREE OF FUZZY A...

引用

2008 International Conference on machine learning and Cybernetics(2008机器学习与控制论国际会议)

作者： XI-ZHAO WANG JUN-HAI ZHAI SU-FANG ZHANG Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Scie Teaching and research of section of mathematics Hebei Information Engineering School Baoding 0710

There may be many fuzzy attributes in a fuzzy information system. Different fuzzy attribute has different contribution to classification. More important attributes have more contribution than the others to decision-making. In this paper, based on the importance of the fuzzy condition attributes, a new method generating a fuzzy decision tree is proposed, which uses the important degree of the fuzzy condition attribute with respect to the fuzzy decision attributes to select attributes to expand the branches of a fuzzy decision tree. A comparison between the new method and fuzzy ID3 is provided. It is shown that the new method is more efficient than fuzzy ID3.

关键词： Condition attribute Decision attribute Fuzzy attribute Fuzzy decision tree Important degree

来源：评论

学校读者我要写书评

暂无评论

IMAGE RECOGNITION BASED ON WAVELET TRANSFORM AND ARTIFICIAL NEURAL NETWORKS

IMAGE RECOGNITION BASED ON WAVELET TRANSFORM AND ARTIFICIAL ...

引用

2008 International Conference on machine learning and Cybernetics(2008机器学习与控制论国际会议)

作者： JUN-HAI ZHAI LI-JUAN LIU SU-FANG ZHANG Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Scie Teaching and research of section of mathematics Hebei Information Engineering School Baoding 07100

This paper proposes an image recognition method, which consists of two steps: features extraction based on wavelet transform and image recognition using artificial neural networks. More specifically, wavelet transform is used to decompose the original image into different frequency sub-bands, then a set of features are extracted from the wavelet coefficients. The feature set as input fed into neural network for recognition. The experimental results confirmed effectiveness of the proposed approach.

关键词： Image recognition Wavelet transform Artificial neural networks Multi-scale features

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：