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

2,966 篇 会议
174 册 图书
25 篇 期刊文献

馆藏范围

3,164 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

2,043 篇 工学
- 1,824 篇 计算机科学与技术...
- 958 篇 软件工程
- 331 篇 电气工程
- 314 篇 信息与通信工程
- 214 篇 控制科学与工程
- 207 篇 生物工程
- 149 篇 生物医学工程（可授...
- 71 篇 光学工程
- 64 篇 机械工程
- 62 篇 化学工程与技术
- 51 篇 电子科学与技术（可...
- 48 篇 仪器科学与技术
- 46 篇 安全科学与工程
- 36 篇 交通运输工程
649 篇 理学
- 353 篇 数学
- 245 篇 生物学
- 139 篇 物理学
- 135 篇 统计学（可授理学、...
- 95 篇 系统科学
- 63 篇 化学
408 篇 管理学
- 244 篇 图书情报与档案管...
- 182 篇 管理科学与工程(可...
- 83 篇 工商管理
262 篇 医学
- 241 篇 临床医学
- 123 篇 基础医学(可授医学...
- 74 篇 药学(可授医学、理...
- 40 篇 公共卫生与预防医...
46 篇 法学
- 42 篇 社会学
38 篇 教育学
- 32 篇 教育学
33 篇 经济学
- 31 篇 应用经济学
23 篇 农学
6 篇 艺术学
4 篇 文学

主题

572 篇 machine learning
563 篇 data mining
320 篇 pattern recognit...
209 篇 deep learning
201 篇 feature extracti...
154 篇 support vector m...
145 篇 artificial intel...
128 篇 machine learning...
120 篇 training
117 篇 accuracy
90 篇 data models
89 篇 data mining and ...
71 篇 neural networks
71 篇 classification
67 篇 predictive model...
66 篇 face recognition
61 篇 learning systems
52 篇 computer imaging...
50 篇 convolutional ne...
48 篇 classification a...

机构

9 篇 school of comput...
9 篇 chinese academy ...
8 篇 zhejiang univers...
8 篇 chitkara univers...
7 篇 guangdong univer...
7 篇 school of inform...
6 篇 xi'an university...
6 篇 indian statistic...
6 篇 central south un...
6 篇 department of co...
6 篇 unsw sydney
6 篇 xi'an university...
6 篇 southern univers...
5 篇 study group aust...
5 篇 peking universit...
4 篇 centre for patte...
4 篇 chongqing univer...
4 篇 national laborat...
4 篇 sun yat sen univ...
4 篇 school of inform...

作者

11 篇 de-shuang huang
8 篇 petra perner
7 篇 krasotkina olga
7 篇 mottl vadim
7 篇 ying tan
6 篇 zheng-guang wu
6 篇 ryszard tadeusie...
6 篇 marcin korytkows...
6 篇 phung dinh
6 篇 venkatesh svetha
6 篇 hongyi li
6 篇 jacek m. zurada
6 篇 chaojie li
6 篇 biao luo
6 篇 ilias maglogiann...
6 篇 lotfi a. zadeh
6 篇 leszek rutkowski
6 篇 lazaros iliadis
6 篇 long cheng
5 篇 vitoantonio bevi...

语言

2,999 篇 英文
152 篇 其他
25 篇 中文
1 篇 土耳其文

检索条件"任意字段=5th International Conference on Machine Learning and Data Mining in Pattern Recognition"

共 3165 条记录，以下是2721-2730 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：

Kernel based learning suitable for text categorization

Kernel based learning suitable for text categorization

引用

SERA 2007: Fifth ACIS international conference on Software Engineering Research, Management, and Applications

作者： Taeho, Jo Malrey, Lee Advanced Graduate Education Center Jeonbuk for Electronics and Information Technology-BK 21 Research Center of Industrial Technology School of Electronics and Information Engineering ChonBuk National University 664-14 1Ga Deok Jin-Dong JeonJu ChonBuk 561-756 Korea Republic of

ISBN: (纸本)0769528678

this research proposes a new strategy where documents are encoded into string vectors for text categorization and modified versions of SVM to be adaptable to string vectors. Traditionally, when the supervised machine learning algorithms are used for pattern classification, raw data should be encoded into numerical vectors. this encoding may be difficult, depending on a given application area of pattern classification. For example, in text categorization, encoding full texts given as raw data into numerical vectors leads to two main problems: huge dimensionality and sparse distribution. In this research, we encode full texts into string vectors, and apply the SVM to string vectors for text categorization. © 2007 IEEE.

关键词： Text processing

来源：评论

学校读者我要写书评

暂无评论

Analysis of Partial Discharge Measurement data Using a Support Vector machine

Analysis of Partial Discharge Measurement Data Using a Suppo...

引用

Student conference on Research and Development (SCOReD)

作者： Nur Fadilah Ab Aziz L. Hao P. L. Lewin Department of Electrical Power Engineering Universiti Tenaga Malaysia (UNITEN) Kajang Selangor Darul Ehsan Malaysia Tony Davies High Voltage Laboratory Electrical Power Engineering Group School of Electronics and Computer Science University of Southampton UK

this paper investigates the recognition of partial discharge sources by using a statistical learning theory, support vector machine (SVM). SVM provides a new approach to pattern classification and has been proven to be successful in fields such as image identification and face recognition. To apply SVM learning in partial discharge classification, data input is very important. the input should be able to fully represent different patterns in an effective way. the determination of features that describe the characteristics of partial discharge signals and the extraction of reliable information from the raw data are the key to acquiring valuable patterns of partial discharge signals. In this paper, data obtained from experiment is carried out in both time and frequency domain. By using appropriate combination of kernel functions and parameters, it is concluded that the frequency domain approach gives a better classification rate.

关键词： Partial discharge measurement Support vector machines Support vector machine classification Partial discharges Frequency domain analysis Statistical learning pattern classification Face recognition data mining Kernel

来源：评论

学校读者我要写书评

暂无评论

Context aware life pattern prediction using fuzzy-state Q-learning

Context aware life pattern prediction using fuzzy-state Q-Le...

引用

5th international conference on Smart Homes and Health Telematics

作者： Feki, Mohamed Ali Lee, Sang Wan Bien, Zeungnam Mokhtari, Mounir Inst Natl Telecommun 9 Rue Charles Fourier F-91011 Evry France Korea Adv Inst Sci & Technol Taejon 305701 South Korea

ISBN: (纸本)9783540730347

In an Assistive Eenvironment (AIE), explicit/obtrusive interfaces for human/computer interaction can demand exclusive user attention and, often, replacement of them with implicit ones embedded into real-world artifacts for intuitive and unobtrusive use is desirable. As a part of solution, Context Aware can be utilized to recognize current context situation from a combination of low-level sensed contexts. Assuming the current context recognized, this paper tackles the next logical step of "the prediction of future contexts". this information allows the system to know patterns and their interrelations in user behaviour, which are not apparent at the lower levels of raw sensor data. the present paper analyzes prerequisites for user-centred prediction of future context and presents an algorithm for autonomous context recognition and prediction, based on our proposed Fuzzy-State Q- learning technique as well as on some established methods for data-based prediction.

关键词： context aware assistive environment prediction fuzzy-state Q-learning

来源：评论

学校读者我要写书评

暂无评论

Parallel nearest neighbour algorithms for text categorization

引用

13th international Euro-Par conference on Parallel Processing

作者： Gil-Garcia, Reynaldo Badia-Contelles, Jose Manuel Pons-Porrata, Aurora Univ Oriente Ctr Pattern Recognit & Data Mining Santiago De Cuba Cuba Univ Jaume 1 Dept Comp Sci & Engn Castellon de La Plana Spain

ISBN: (纸本)9783540744658

In this paper we describe the parallelization of two nearest neighbour classification algorithms. Nearest neighbour methods are well-known machine learning techniques. they have been successfully applied to Text Categorization task. Based on standard parallel techniques we propose two versions of each algorithm on message passing architectures. We also include experimental results on a cluster of personal computers using a large text collection. Our algorithms attempt to balance the load among the processors, they are portable, and obtain very good speedups and scalability.

关键词： Parallel processing systems

来源：评论

学校读者我要写书评

暂无评论

Variable Width Elliptic Gaussian Kernels for Probability Density Estimation

Variable Width Elliptic Gaussian Kernels for Probability Den...

引用

international conference on Telecommunications in Modern Satellite, Cable and Broadcasting Service (TELSIKS)

作者： Dragoljub Pokrajac Longin Jan Latecki Aleksandar Lazarevic Jelena Nikolic Computer and Information Science Department Applied Mathematics Research Center and Center for Research and Education in Optical Sciences and Applications (CREOSA) Delaware State University Dover DE USA CIS Department Temple University Philadelphia PA USA CREOSA and United Technologies Research Center Hartford CT USA Faculty of Electronic Engineering University of Nis Nis Serbia

Estimation of probability density functions based on available data is important problem arising in various fields, such as telecommunications, machine learning, data mining, pattern recognition and computer vision. In this paper, we consider Kernel-based non-parametric density estimation methods and derive formulae for variable kernel density estimation using generalized, elliptic Gaussian kernels. the proposed technique is verified on simulated data.

关键词： Kernel Probability density function machine learning data mining pattern recognition Computer vision Eigenvalues and eigenfunctions Random variables State estimation Optical computing

来源：评论

学校读者我要写书评

暂无评论

learning by Bagging and Adaboost based on Support Vector machine

Learning by Bagging and Adaboost based on Support Vector Mac...

引用

IEEE international conference on Industrial Informatics (INDIN)

作者： Yu Wang Cheng De Lin Department of Automation Xiamen University Xiamen China

Ensemble of classifiers (Multiple classifier system) and Support Vector machine (SVM) are now well established research lines in machine learning. Recently, some works devoted to SVM-based ensembles report that the most popular ensembles creation methods Bagging and Adaboost are not expected to improve the performance of SVMs and sometimes they even worsen the performance, due to that SVM is stable and strong classifier. In this paper, we focus on adapting Bagging and Adaboost to SVM. the framework of Bagging is extended by introducing the Class-wise expert classifiers, then we proposed the improved algorithm CeBag. the weighting rule of AdaBoost is modified to deal with the overfitting problem which may be even worse when boosting strong classifiers, and the strength of SVM is weakened by adaptively adjusting the kernel parameters, then we proposed the algorithm WwBoost. Experiments implemented on IDA benchmark data sets show that our algorithms are effective in building ensemble of SVMs.

关键词： machine learning Bagging Support vector machines Support vector machine classification Kernel pattern recognition Automation Electronic mail Boosting Risk management

来源：评论

学校读者我要写书评

暂无评论

A Novel Ensemble Strategy for Classification of Prostate Cancer Protein Mass Spectra

A Novel Ensemble Strategy for Classification of Prostate Can...

引用

29th Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2007), vol.15

作者： Amin Assareh Mohammad Hassan Moradi Vahid Esmaeili Biomedical Engineering Amirkabir University of Technology슠 Tehran Iran Biomedical Signal and Image Processing Laboratory (BiSIPL) School of Electrical Engineering Sharif University of Technology Iran

Protein mass spectra pattern recognition is a new forum, in which many machine learning algorithms have been conducted to enhance the chance of early cancer diagnosis. the high-dimensionality-small-sample (HDSS) problem of cancer proteomic datasets still requires more sophisticated approaches to improve the classification accuracy. In this study we present a simple ensemble strategy based on measuring the generalizing capability of different subsets of training data and apply it in making final decision. Using a limited number of biomarkers along with 5 classification algorithms, the proposed method achieved a promising performance over a well-known prostate cancer mass spectroscopy dataset.

关键词： Prostate cancer Proteins machine learning algorithms Proteomics Biomarkers Cancer detection Classification algorithms Mass spectroscopy data mining pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Outlier Identification and Justification Using Multi-Objective PSO based Clustering Algorithm in Power System

Outlier Identification and Justification Using Multi-Objecti...

引用

IEEE international conference on Industrial Informatics (INDIN)

作者： Li Feng Ziyan Liu Chao Ma Power Dispatching & Transaction Center Chongqing Electrical Power Corporation Computer Science and Communication Technology Guizhou University Chongqing Electric Power Corporation Chongqing China

A clustering method based on multi-objective PSO is developed in this paper for bad data identification. the algorithm automatically determines the optimum number of clusters and it starts by partitioning the data set into a relatively large number of clusters to reduce the effects of initial conditions. After the bad data are detected, eigencurves of correlating load extracted by Kohonen network are used to modify the bad data. the application of the proposed clustering algorithm to the problem of unsupervised classification of electric load data is investigated. through the simulation test, the results show the effectiveness of the algorithm.

关键词： Clustering algorithms Power systems Partitioning algorithms Particle swarm optimization Power system security Shape data mining Power system simulation machine learning algorithms Chaos

来源：评论

学校读者我要写书评

暂无评论

Toward Building Lightweight Intrusion Detection System through Modified RMHC and SVM

Toward Building Lightweight Intrusion Detection System Throu...

引用

IEEE international conference on Networks

作者： You Chen Wen-Fa Li Xue-Qi Cheng Graduate University Chinese Academy and Sciences China Chinese Academy of Sciences Beijing Beijing CN Institute of Computing Technology Chinese Academy and Sciences China

ISBN: (纸本)9781424412297;1424412293

Feature selection attracted much interest from researchers in many fields such as network security, pattern recognition and data mining. In this paper, we present a wrapper-based feature selection algorithm aiming at modeling lightweight intrusion detection system (IDS) by (1) using modified random mutation hill climbing (MRMHC) as search strategy to specify a candidate subset for evaluation; (2) using support vector machines (SVMs) as wrapper approach to obtain the optimum feature subset. We have examined the feasibility of our feature selection algorithm by conducting several experiments on KDD 1999 intrusion detection dataset which was categorized as DOS, PROBE, R2L and U2R. the experimental results show that our approach is able not only to speed up the process of selecting important features but also to guarantee high detection rates. Furthermore, our experiments indicate that intrusion detection system with a combination of our proposed approach has smaller computational resources than that with GA-SVM which is a popular feature selection algorithm in the field.

关键词： Intrusion detection Support vector machines Filters Computational complexity machine learning algorithms Genetic algorithms Support vector machine classification Accuracy Computers Optimization methods

来源：评论

学校读者我要写书评

暂无评论

Performance Improvement of Bankruptcy Prediction using Credit Card Sales Information of Small & Micro Business

Performance Improvement of Bankruptcy Prediction using Credi...

引用

international conference on Software Engineering Research, Management and Applications (SERA)

作者： Jongsik Yoon Young S. Kwon Tae Hyup Roh Dongguk University South Korea Seoul Woman University South Korea

Due to the poor financial statements which represent credit risk of small and micro business, it's been difficult to develop the credit evaluation model that reflects both consumer credit risk and business credit risk of small and micro business. the purpose of this study is to develop the credit evaluation model for small and micro businesses using credit card sales information in lieu of poor financial information. In order to develop the model, we derive some variables and analyze the relationship between good and bad credits. We find out that twelve variables are significant in predicting good or bad risk for small and micro business, which are categorized into the business period, scale for sale, a fluctuation in sales, sales pattern and business category's bankruptcy ratio, etc. We employ the new statistical learning technique, support vector machines (SVM) as a classifier. We use grid search technique to find out better parameter for SVM. the experimental result shows that credit card sales information could be a good substitute for the financial data on business credit risk in predicting the bankruptcy for small-micro businesses. In addition, we also find out that SVM performs best, when compared with other classifiers such as neural networks, CART, C5.0, multivariate discriminant analysis (MDA), and logistic regression analysis (IRA).

关键词： Credit cards Marketing and sales Support vector machines Support vector machine classification Fluctuations Statistical learning Neural networks Performance analysis Logistics Regression analysis

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317页 << < 269 270 271 272 273 274 275 276 277 278 > >>

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：