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

23,359 篇 会议
2,934 篇 期刊文献
16 篇 学位论文

馆藏范围

26,309 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

5,648 篇 工学
- 3,392 篇 计算机科学与技术...
- 3,142 篇 电气工程
- 1,808 篇 信息与通信工程
- 640 篇 控制科学与工程
- 538 篇 软件工程
- 481 篇 仪器科学与技术
- 300 篇 机械工程
- 300 篇 测绘科学与技术
- 284 篇 生物医学工程（可授...
- 148 篇 电子科学与技术（可...
- 114 篇 生物工程
- 108 篇 交通运输工程
- 107 篇 环境科学与工程（可...
- 75 篇 网络空间安全
- 56 篇 航空宇航科学与技...
- 43 篇 材料科学与工程（可...
841 篇 理学
- 194 篇 物理学
- 158 篇 生物学
- 137 篇 地球物理学
- 124 篇 数学
- 122 篇 系统科学
- 96 篇 地理学
- 50 篇 化学
- 42 篇 统计学（可授理学、...
526 篇 管理学
- 481 篇 管理科学与工程(可...
493 篇 医学
- 369 篇 临床医学
- 100 篇 基础医学(可授医学...
195 篇 农学
- 99 篇 作物学
- 80 篇 农业资源与环境
75 篇 文学
- 70 篇 新闻传播学
23 篇 教育学
21 篇 经济学
19 篇 艺术学
13 篇 法学
7 篇 军事学
2 篇 历史学

主题

26,309 篇 classification a...
6,463 篇 feature extracti...
5,177 篇 training
4,677 篇 accuracy
4,372 篇 support vector m...
3,194 篇 machine learning...
2,671 篇 prediction algor...
2,638 篇 clustering algor...
2,490 篇 algorithm design...
2,350 篇 data mining
2,253 篇 machine learning
1,593 篇 data models
1,402 篇 deep learning
1,358 篇 optimization
1,338 篇 decision trees
1,172 篇 predictive model...
1,164 篇 testing
1,138 篇 computational mo...
1,094 篇 neural networks
1,020 篇 databases

机构

63 篇 chitkara univers...
23 篇 centre of resear...
23 篇 college of infor...
19 篇 school of comput...
18 篇 tsinghua univers...
18 篇 university of ch...
17 篇 chitkara centre ...
17 篇 school of inform...
17 篇 department of co...
16 篇 school of comput...
16 篇 school of comput...
16 篇 school of electr...
14 篇 computer science...
14 篇 univ chinese aca...
14 篇 microsoft resear...
14 篇 school of comput...
13 篇 school of electr...
13 篇 school of electr...
13 篇 school of comput...
12 篇 department of in...

作者

29 篇 wei li
22 篇 hui wang
22 篇 jun wang
21 篇 lei wang
17 篇 xia sun
17 篇 yang yang
16 篇 jing zhang
15 篇 jun zhang
15 篇 liu yang
14 篇 xi chen
14 篇 li zhang
14 篇 jie li
13 篇 jian wang
13 篇 rakesh kumar
13 篇 jie yang
13 篇 jun shi
13 篇 chen chen
12 篇 bing xue
12 篇 ahmad jalal
12 篇 xuegang hu

语言

26,172 篇 英文
91 篇 其他
33 篇 中文
4 篇 土耳其文
2 篇 法文
1 篇 西班牙文
1 篇 俄文

检索条件"主题词=CLASSIFICATION algorithms"

共 26309 条记录，以下是111-120 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：

Examining the performance of classification algorithms for imbalanced data sets in web author identification

Examining the performance of classification algorithms for i...

引用

Open Innovations Association and Seminar on Information Security and Protection of Information Technology (FRUCT-ISPIT), Conference of

作者： Alisa A. Vorobeva ITMO University St. Petersburg Russia

ISBN: (纸本)9781509025008

Individuals, criminals or even terrorist organizations can use web-communication for criminal purposes; to avoid the prosecution they try to hide their identity. To increase level of safety in Web we have to improve the author (or web-user) identification and authentication procedures. In field of web author identification the situation of imbalanced data sets appears rather frequent, when number of one author's texts significantly exceeds the number of other's. This is common situation for the modern web: social networks, blogs, emails etc. Author identification task is some sort of classification task. To develop methods, technics and tools for web author identification we have to examine the performance of classification algorithms for imbalanced data sets. In this work several modern classification algorithms were tested on data sets with various levels of class imbalance and different number of available webpost The best accuracy in all experiments was achieved with Random Forest algorithm.

关键词： classification algorithms Training Support vector machines Blogs Text categorization Logistics Authentication

来源：评论

学校读者我要写书评

暂无评论

Synthesis of classification algorithms of the Quasi-Deterministic Signals with Random Parameters

Synthesis of Classification Algorithms of the Quasi-Determin...

引用

Microwave Conference (RMC), All-Russian

作者： Vladimir Mikhaylovich Artyushenko Vladimir Ivanovich Volovach Information technology and management systems department Technological University Korolev city Russian Federation Informational and electronic service department Volga Region State University of Service Togliatty city Russian Federation Voronezh State University Voronezh city Russian Federation

ISBN: (数字)9798331540944

ISBN: (纸本)9798331540951

The problem of synthesis of the algorithms for classifying quasi-deterministic signals with random parameters is considered. The need to solve such a problem is associated with the widespread occurrence of signal processing cases where the average likelihood ratio is not expressed through elementary functions. It is shown that the process of calculating the statistics of the average likelihood ratio can be represented by a sequence of elementary transformations of input influence samples. Expressions are found for determining asymptotically sufficient statistics when solving radio engineering problems, including possible simplifications for certain conditions. The corresponding block diagrams of computers have been obtained, allowing them to work when both the noise environment and the parameters of useful signals change. An approximate expression for the unconditional likelihood ratio for a wide class of probability distributions of input values and random parameters of signals is found. classification algorithms are given and their quality is assessed.

关键词： Computers Computational modeling Noise Integral equations Signal processing algorithms Probabilistic logic Probability distribution Mathematical models classification algorithms Structural engineering

来源：评论

学校读者我要写书评

暂无评论

How to effectively utilize information to design hyperspectral target detection and classification algorithms

How to effectively utilize information to design hyperspectr...

引用

IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data

作者： Chein-I Chang Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA

ISBN: (纸本)0780383508

Hyperspectral imagery offers a means of uncovering enormous spectral information that can be used for various applications in data exploitation. How effectively such information is used affects the way image analysis algorithms are designed. In this paper, we take up this issue and focus on algorithms designed and developed for target detection and classification in hyperspectral imagery. In order to effectively characterize the information available before and after the data are processed, the a priori information and a posteriori information are used in accordance with how the information is obtained. A piece of information is referred to as a priori information if it is provided by known knowledge before data are processed. On the other hand, a piece of information is referred to as a posteriori information if it is unknown a priori, but can be obtained directly from the data in an unsupervised fashion during the course of data processing. Since a priori information is known beforehand, it can be further decomposed into two types of information, desired and undesired a priori information. The desired a priori information is the knowledge that will assist, improve and enhance data analysis, whereas the undesired a priori information is the knowledge that hinders, interferes or destructs analysis during data processing. This paper investigates how these three types of information play their roles in design and development of several hyperspectral target detection and classification algorithms. Experiments are also conducted to validate their utility.

关键词： Algorithm design and analysis Object detection classification algorithms Hyperspectral imaging Data processing Data analysis Hyperspectral sensors Image analysis Information analysis Interference constraints

来源：评论

学校读者我要写书评

暂无评论

The effect of training data on hyperspectral classification algorithms

The effect of training data on hyperspectral classification ...

引用

IEEE Signal Processing and Communications Applications (SIU)

作者： Okan Bilge Özdemir Yasemin Yardımcı Çetin Enformatik Enstitüsü Orta Doğu Teknik Üniversitesi Ankara Turkey

In this study, the performance of different hyperspectral classification algorithms with the same training set is investigated. In addition, the effect of the dimension and sampling strategy for the training set selection is demonstrated. Support Vector Machines (SVM), K- Nearest Neighbor (K-NN) and Maximum Likelihood (ML) methods are used. The contribution of using spatial information with spectral information is observed. Meanshift segmentation and window weighting methods are used for spatial information. High resolution Pavia University hyperspectral data and Indian Pines data are used in this study.

关键词： Hyperspectral imaging Support vector machines Kernel classification algorithms Training

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Results of Modern classification algorithms Usage for Determining the Type of Physical Activity Based on Integrated Sensors Data

Comparative Analysis of Results of Modern Classification Alg...

引用

Wave Electronics and its Application in Information and Telecommunication Systems (WECONF)

作者： A. V. Agranovskii A. P. Silukov Saint-Petersburg State University of Aerospace Instrumentation Saint Petersburg Russia

The article considers the usage of various classification algorithms to process data from integrated sensors of a modern smartphone to obtain user's physical activity. To compare classification algorithms, we use modeling based on a dataset from an experiment that has 561 significant characteristics for each type of activity with a total number of records equal to 10299. The analysis of data from integrated sensors is performed by several classification algorithms: decision trees, Random Forest algorithm, logistic regression, support vector machine with a linear function and a kernel function. In addition to pure (without modification) ones, algorithms with preliminary optimization of hyperparameters using random search and cross-validation are used. The evaluation metrics are: Accuracy, Precision, Recall, F-measure, Mean Absolute Error and Root Mean Square Error. The estimated metrics and confusion matrices obtained using specially written python scripts using the sklearn library are provided for each algorithm. Analysis of the presented results shows that the best classification results both with preliminary optimization of hyperparameters and cross-validation, and without preliminary tuning, are provided by the use of linear support vector machine algorithm.

关键词： Measurement Support vector machine classification Sensor phenomena and characterization classification algorithms Telecommunications Root mean square Regression tree analysis

来源：评论

学校读者我要写书评

暂无评论

Review of Brain Tumor Segmentation, Detection and classification algorithms in fMRI Images

Review of Brain Tumor Segmentation, Detection and Classifica...

引用

International Conference on Computational and Characterization Techniques in Engineering & Sciences (CCTES)

作者： Tom Philip Pries Roshan Jahan Preetam Suman Universität Osnabrück Osnabrück Germany Integral University Lucknow India

ISBN: (纸本)9781538642559;9781538642542

Nowadays Brain tumor detection in early stage is necessary because many people died due to unawareness of having a brain tumor. On the other side influence of machine learning becomes larger and larger in our lifes and our society, artificial intelligence might also start playing an important role in medical diagnosis and support of doctors and surgeons. This paper is focused on review of those papers which include segmentation, detection and classification of brain tumors. The common procedure for an algorithm which aims to classify brain tumors on fMRI or MRI scans is: Preprocessing the image for example by removing noise, then segmenting the image, which yields the region which might be a brain tumor, and finally classifying features such as inten-sity, shape and texture of this region. Many machine learning approaches towards brain tumor detection have already been made. However, these approaches, even though yielding good results, are not used yet. Therefore this research topic remains important and still requires attention.

关键词： Tumors Feature extraction Image segmentation classification algorithms Functional magnetic resonance imaging Support vector machines Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

Polynomial classification algorithms for Markov decision processes

Polynomial classification algorithms for Markov decision pro...

引用

IEEE Conference on Decision and Control

作者： Eugene A. Feinberg Fenghsu Yang Department of Applied Math and Statistics State University of New York Stony Brook NY USA

ISBN: (纸本)9781424431236

The unichain classification problem detects whether an MDP with finite states and actions is unichain or not under all deterministic policies. This problem has been proven to be NP-hard. This paper provides polynomial algorithms for this problem while there exists a state in an MDP, which is either recurrent under all deterministic policies or absorbing under some action.

关键词： Polynomials classification algorithms State-space methods Stochastic processes Statistics Inventory control

来源：评论

学校读者我要写书评

暂无评论

Comparative Study on Data Mining classification algorithms for Predicting Road Traffic Accident Severity

Comparative Study on Data Mining Classification Algorithms f...

引用

International Conference on Inventive Communication and Computational Technologies (ICICCT)

作者： Tadesse Kebede Bahiru Dheeraj Kumar Singh Engdaw Ayalew Tessfaw Dept. of Information Technology Parul University Vadodara Gujarat India

According to World Health Organization report the number of deaths by road traffic accident is more than 1.25 million people and every year with non-fatal accidents affecting more than 20-50 million people. Several factors are contributed on the occurrence of road traffic accident. In this study, data mining classification techniques applied to establish models (classifiers) to identify accident factors and to predict traffic accident severity using previously recorded traffic data. Using WEKA (Waikato Environment for Knowledge Analysis) data mining decision tree (J48, ID3 and CART) and Naïve Bayes classifiers are built to model the severity of injury. The classification performance of all these algorithms is compared based on their results. The experimental result shows that the accuracy of J48 classifier is higher than others.

关键词： Accidents classification algorithms Roads Decision trees Prediction algorithms Data mining Training

来源：评论

学校读者我要写书评

暂无评论

Prediction of protein – peptide binding residues using classification algorithms

Prediction of protein – peptide binding residues using clas...

引用

IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Shima Shafiee Abdolhossein Fathi Fardin Abdali Mohammadi RAZI UNIVERSITY Kermanshah Iran

ISBN: (数字)9781728195742

ISBN: (纸本)9781728195759

Peptide-binding proteins prediction is important in understanding biological interaction, protein performance analysis, cellular processes, drug design, and even cancer prediction, so using experimental predictive methods, despite their operational capabilities, has limitations such as being costly and need to spend more time, differences between unrecognized protein structures and sequences, so design and development of computational systems for maintenance, optimal models for representing biological knowledge, management and the analysis of big biological data is so important that the authors used machine learning-based techniques such as Support Vector Machine (SVM),Random Forest (RF),Decision Tree (C4.5), Decision Tree (ID3),Gradient Boosting classifiers, which evaluated experimental results to optimize Support Vector Machine(SVM) classifier (Radial Basis Function kernel) with significant evaluation parameters such as accuracy(ACC) is equal to 0.7401 and 0.7599 for 10-fold cross validation and independent test set and also specificity (SPE) is equal to 0.7966 and 0.8088 for 10-fold cross validation and independent test set (respectively) by using various Structure-Based and Sequence-Based features.

关键词： Proteins Support vector machine classification Vegetation Predictive models Prediction algorithms classification algorithms Performance analysis

来源：评论

学校读者我要写书评

暂无评论

Comparison of classification algorithms for Alzheimer’s Disease Prediction

Comparison of Classification Algorithms for Alzheimer’s Dis...

引用

International Conference on Parallel Distributed and Grid Computing (PDGC)

作者： Harshit Saxena Divyansh Joshi Hari Singh Rohit Anand Computer Science & Engineering Department Jaypee University of Information Technology Solan Himachal Pradesh India ECE Department G.B.Pant DSEU Okhla-1 Campus New Delhi India

ISBN: (纸本)9781665454025

The application of machine learning to investigate metabolic disorders like diabetes and Alzheimer's Disease (AD), which impact significant populations of people worldwide, is currently receiving a lot of attention. Early on, AD was challenging to predict. The method of identifying the parameters that were most effective for predicting Alzheimer's disease involved the use of decision trees, support vector machines, XGBoost, random forest, extra trees, AdaBoost, gradient boosting, and voting classifiers. In this research, the Extra Trees classifier has been used which, from our research, has rarely been explored in the past. This classifier gives the best results in terms of performance among all the implemented techniques. The performance is evaluated using evaluation parameters such as precision, recall, F1-Score and accuracy. Using these machine learning methods, especially the Extra Trees algorithm, for early identification of Alzheimer’s disease will greatly benefit in lowering the annual mortality rate caused by AD.

关键词： Support vector machines Machine learning algorithms Sociology Prediction algorithms Feature extraction classification algorithms Reliability

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500页 << < 8 9 10 11 12 13 14 15 16 17 > >>

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：