检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

78 篇 会议
10 篇 期刊文献

馆藏范围

88 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

58 篇 工学
- 50 篇 计算机科学与技术...
- 48 篇 软件工程
- 30 篇 控制科学与工程
- 9 篇 信息与通信工程
- 3 篇 机械工程
- 2 篇 化学工程与技术
- 1 篇 动力工程及工程热...
- 1 篇 建筑学
- 1 篇 土木工程
- 1 篇 农业工程
- 1 篇 环境科学与工程（可...
37 篇 管理学
- 29 篇 管理科学与工程(可...
- 13 篇 图书情报与档案管...
- 1 篇 工商管理
35 篇 理学
- 30 篇 数学
- 9 篇 系统科学
- 6 篇 统计学（可授理学、...
- 2 篇 化学
- 1 篇 物理学
1 篇 文学
- 1 篇 新闻传播学
1 篇 农学
- 1 篇 作物学

主题

10 篇 support vector m...
4 篇 rough set
4 篇 fuzzy measure
4 篇 decision trees
3 篇 support vector m...
3 篇 random variables
3 篇 dominance relati...
3 篇 fuzzy integral
3 篇 classification a...
3 篇 classification (...
3 篇 training
2 篇 information syst...
2 篇 core vector mach...
2 篇 rough sets
2 篇 approximation al...
2 篇 core set
2 篇 noise measuremen...
2 篇 decision tree
2 篇 variable precisi...
2 篇 extended dominan...

机构

23 篇 key lab. of mach...
9 篇 key lab.of machi...
6 篇 college of mathe...
6 篇 key lab.of machi...
5 篇 key lab.in machi...
4 篇 key lab of machi...
4 篇 key lab. of mach...
4 篇 key lab. of mach...
3 篇 key lab. in mach...
3 篇 college of scien...
3 篇 center for machi...
3 篇 department of in...
3 篇 key lab. in mach...
2 篇 beijing key lab ...
2 篇 key laboratory o...
2 篇 college of mathe...
2 篇 key lab. in mach...
2 篇 key lab of high ...
2 篇 beijing academy ...
2 篇 graduate univers...

作者

9 篇 yan li
9 篇 li yan
8 篇 xi-zhao wang
5 篇 yuan fang
4 篇 yan zhan
4 篇 jun-hai zhai
4 篇 su-fang zhang
4 篇 jun-fen chen
3 篇 li zhao
3 篇 zhan yan
3 篇 guo-fang zhang
3 篇 wang xizhao
3 篇 zhai jun-hai
3 篇 lu shuxia
3 篇 qun-feng zhang
3 篇 chen hao
3 篇 shuxia lu
3 篇 ai-xia chen
3 篇 zhai junhai
3 篇 ning li

语言

87 篇 英文
1 篇 其他

检索条件"机构=Key Lab.of Machine Learning and Computational Intelligence"

共 88 条记录，以下是31-40 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

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

A NEW HEURISTIC OF THE DECISION TREE INDUCTION

A NEW HEURISTIC OF THE DECISION TREE INDUCTION

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： NING LI LI ZHAO AI-XIA CHEN QING-WU MENG GUO-FANG ZHANG Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 Hebei China

Decision tree induction is one of the useful approaches for extracting classification knowledge from a set of feature-based instances. The most popular heuristic information used in the decision tree generation is the minimum entropy. This heuristic information has a serious disadvantage-the poor generalization capability [3]. Support Vector machine (SVM) is a classification technique of machine learning based on statistical learning theory. It has good generalization. Considering the relationship between the classification margin of support vector machine(SVM) and the generalization capability, the large margin of SVM can be used as the heuristic information of decision tree, in order to improve its generalization *** paper proposes a decision tree induction algorithm based on large margin heuristic. Comparing with the binary decision tree using the minimum entropy as the heuristic information, the experiments show that the generalization capability has been improved by using the new heuristic.

关键词： Decision tree Support vector machines SMO Clustering large margin Generalization

来源：评论

学校读者我要写书评

暂无评论

An improved research method about the similarity calculation of ontology

An improved research method about the similarity calculation...

引用

2009 International Conference on Information Engineering and Computer Science, ICIECS 2009

作者： Li, Xin-Fu Yin, Peng Zheng, Mei Key Lab. in Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding China Institute of International Education Yanshan University Qinhuangdao China

ISBN: (纸本)9781424449941

Ontology mapping has been widely used in ontology application, but the similarity calculation becomes a thorny issue in the process of ontology mapping. In this paper, the different elements of ontology are considered. Semantic similarity and concept similarity are integrated to get the ontology similarity. During the similarity calculation of the concept attributes, filter strategy is used to reduce the number of concept attributes, and a method of attributes similarity calculation is proposed. In addition, comprehensive similarity calculation method is given including the semantic and the concept of ontology. The experiment results show that this approach can improve the precision effectively. ©2009 IEEE.

关键词： Ontology

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

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

来源：评论

学校读者我要写书评

暂无评论

Markov property of Markov chains and its test

Markov property of Markov chains and its test

引用

International Conference on machine learning and Cybernetics

作者： Zhang, Yu-Fen Zhang, Qun-Feng Yu, Rui-Hua Key Lab. for Machine Learning and Computational Intelligence College of Mathematics and Computer Hebei University Baoding 071002 China Department of Information Technology Baoding University Baoding 071000 China

ISBN: (纸本)9781424465262

Markov chains, with Markov property as its essence, are widely used in the fields such as information theory, automatic control, communication techniques, genetics, computer sciences, economic administration, education administration, and market forecasts. While using Markov chains to predict the future events, we must test the Markov property of random variable sequences of the past statistic data. Only when the random variable sequences satisfy the Markov property, can the prediction could be precise. This paper discusses the concept of Markov property and its features, studies its test method, and by example demonstrates the effectiveness of this prediction method. © 2010 IEEE.

关键词： Random variables

来源：评论

学校读者我要写书评

暂无评论

Feature extended short text categorization based on theme ontology

Feature extended short text categorization based on theme on...

引用

2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012

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

ISBN: (纸本)9781467300223

Short text classification problem as text classification a branch, in addition to the same with traditional text classification to a certain degree, still need to face some special problems to be solved, because of short text length, features sparse, measuring the words difficultly. Due to the nature of ontology emphasize related field concept, which has the defect of few characteristics in short text, it is necessary to emphasize the relationship between semantic. This paper uses the feature extended method based on theme Ontology. As considering the semantic relations, it can get better classification performance compared to the conventional method. Meanwhile, using Case-Base Maintenance learning via the GC (Generalization Capability) algorithm, which can reduce the case number into K-NN algorithm, can improve efficiency when indexing near neighbor in K-Nearest Neighbor algorithm. The numerical experiments prove the validity of this learning algorithm. © 2012 IEEE.

关键词： Ontology

来源：评论

学校读者我要写书评

暂无评论

Chinese text categorization study based on CBM learning

Chinese text categorization study based on CBM learning

引用

2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010

ISBN: (纸本)9781424459346

Text Categorization (TC) is an important component in many information organization and information management tasks. In many TC applications, the case-base grows at a fast rate and this causes inefficiency in the case retrieval process. Using Case-Base Maintenance learning via the GC (Generalization Capability) altorithm, which can reduce the case number into KNN algorithm, can improve efficiency when indexing near neighbor in K-Nearest Neighbor algorithm. The numerical experiments prove the validity of this learning algorithm. Since K-NN algorithm is used extensively to a variety of areas, we can improve classification performance further in TC. ©2010 IEEE.

关键词： Information management

来源：评论

学校读者我要写书评

暂无评论

A DYNAMIC FUZZY MEASURE FOR MULTIPLE CLASSIFIER FUSION

A DYNAMIC FUZZY MEASURE FOR MULTIPLE CLASSIFIER FUSION

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： YA-JING ZHANG XUE-FEI LI JUN-FEN CHEN HUI-MIN FENG College of Science Agricultural University of Hebei Baoding 071001 China Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Scie

It has been shown that the fuzzy integral is an effective tool for the fusion of multiple classifiers. Of primary importance in the development of the system is the choice of the measure which embodies the importance of subsets of classifiers. In this paper we propose a method for a dynamic fuzzy measure which will change following the pattern to be classified (data dependent). This method uses the neural network which has good study ability. Our experiment results show that this method make the classification accurate improve.

关键词： Multiple classifier Fusion Fuzzy measure Fuzzy integral Neural network

来源：评论

学校读者我要写书评

暂无评论

A comparative study of four Fuzzy Integrals for classifier fusion

A comparative study of four Fuzzy Integrals for classifier f...

引用

International Conference on machine learning and Cybernetics

作者： Feng, Hui-Min Li, Xue-Fei Chen, Jun-Fen Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China College of Science Agricultural University of Hebei Baoding 071001 China

ISBN: (纸本)9781424465262

Fuzzy Integral is widely accepted and applied in multi-classifier fusion to express the importance of individual classifiers and the interaction among classifiers. In this fusion model, there are two keys to determine. One is determining the fuzzy measure. Many researchers have done much work and proposed many types of fuzzy measure and methods to determine fuzzy measures. Another is selecting from four types of fuzzy integral: Sugeno integral, Choquet integral, upper integral and lower integral. Usually, the type of fuzzy integral is specified in advance. Choquet integral is often the choice. This paper is to compare comprehensively four fuzzy integrals in multiple-classifier fusion and hope to give the foundation for selecting Choquet integral. According the theoretical and experimental analysis, it gives the conclusion that Choquet integral is the best suitable for classifier fusion. © 2010 IEEE.

关键词： Integral equations

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共9页 << < 1 2 3 4 5 6 7 8 9 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：