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

23,360 篇 会议
2,978 篇 期刊文献
16 篇 学位论文

馆藏范围

26,354 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

5,693 篇 工学
- 3,419 篇 计算机科学与技术...
- 3,186 篇 电气工程
- 1,829 篇 信息与通信工程
- 643 篇 控制科学与工程
- 538 篇 软件工程
- 488 篇 仪器科学与技术
- 305 篇 测绘科学与技术
- 300 篇 机械工程
- 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...
- 41 篇 材料科学与工程（可...
849 篇 理学
- 194 篇 物理学
- 160 篇 生物学
- 141 篇 地球物理学
- 126 篇 数学
- 122 篇 系统科学
- 97 篇 地理学
- 51 篇 化学
- 43 篇 统计学（可授理学、...
526 篇 管理学
- 481 篇 管理科学与工程(可...
498 篇 医学
- 374 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

26,354 篇 classification a...
6,478 篇 feature extracti...
5,192 篇 training
4,697 篇 accuracy
4,379 篇 support vector m...
3,199 篇 machine learning...
2,675 篇 prediction algor...
2,641 篇 clustering algor...
2,490 篇 algorithm design...
2,356 篇 data mining
2,259 篇 machine learning
1,603 篇 data models
1,405 篇 deep learning
1,361 篇 optimization
1,338 篇 decision trees
1,174 篇 predictive model...
1,165 篇 testing
1,140 篇 computational mo...
1,096 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 princess nourah ...

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

26,217 篇 英文
90 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 26354 条记录，以下是171-180 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：

Algorithm Evaluation for classification “Phishing Website” Using Several classification algorithms

Algorithm Evaluation for Classification “Phishing Website”...

引用

International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Rizki Wahyudi Hendra Marcos Uswatun Hasanah Bambang Pilu Hartato Tri Astuti Rizal Anjas Prasetyo Departement of Informatics Engineering STMIK Amikom Purwokerto Purwokerto Indonesia

ISBN: (纸本)9781538670835;9781538670828

Phishing websites are a fooling technique by making victims as if they are accessing legitimate sites. Data mining is a technique for extracting hidden information in order to benefit more from existing data. Data mining is the process of discovering regularity, patterns, and relationships in large datasets. In this study, data mining will be used to determine the effect of feature selection on algorithm C4.5 and CART on phishing website dataset. From the tests that have been done the effect of feature selection on the phishing website, dataset proved to overcome the longer computational time. From the performance measurement of both algorithms that have been done, CART algorithm has a higher accuracy value than the algorithm C4.5 with an accuracy of 94.4%, while the algorithm C4.5 has an accuracy of 94.3%, so it can be concluded that CART algorithm has better performance value compared with the C4.5 algorithm.

关键词： Phishing Data mining classification algorithms Feature extraction Databases Decision trees Information technology

来源：评论

学校读者我要写书评

暂无评论

Predicting Grade Promotion Using Decision Tree and Naïve Bayes classification algorithms

Predicting Grade Promotion Using Decision Tree and Naïve Ba...

引用

International Conference on Informatics and Computing (ICIC)

作者： Eni Irfiani Instianti Elyana Fintri Indriyani Frans Eduard Schaduw Danang Dwi Harmoko Information Systen Universitas Bina Sarana Informatika Jakarta Indonesia Office Administration Universitas Bina Sarana Informatika Jakarta Indonesia Information System Universitas Bina Sarana Informatika Jakarta Indonesia English Letters Universitas Bina Sarana Informatika Jakarta Indonesia

ISBN: (纸本)9781538669228

The rapid development of the digital era is now a major challenge for the education system in Indonesia, especially for high school students. Today's teenagers are in a digital age where the development and enhancement of knowledge in the field of digital technology has had a dramatic impact. Common problems faced by senior high school students include their social relationship, difficulty concentrating in learning, lack of discipline, disobedience to orderliness and disrespect toward teacher and friends. Of these problems have an impact that the student's value is less than the average so that students become class. For that reason, we need a solution to reduce the number of students who failing a grade. Data mining concerns the education world to improve the quality of education by minimizing the number of failing grade students. classification techniques on data mining used to process data that is Decision Tree and Naïve Bayes. Many data can be managed in schools using the method of data mining, therefore it is necessary to limit the problem so that the assessment can be focused and not floating. Limitations in the problem include Cognitive values, Psychomotor values, Affective values, Number of attendance Number of remedial exams. The results of the analysis will be used to predict the class increase that will affect the quality improvement of students in the future. Measurement results using confusion matrix and ROC curve obtained decision tree accuracy values of 97.5% and naïve bayes of 97.5%.

关键词： Decision trees Data mining classification algorithms Training Software algorithms Prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

Prediction of Liver Disease using classification algorithms

Prediction of Liver Disease using Classification Algorithms

引用

International Conference on Computing, Communication & Automation (ICCCA)

作者： k. Thirunavukkarasu Ajay S. Singh Md Irfan Abhishek Chowdhury School of Computer Science and Engineering Galgotias University Greater Noida India

ISBN: (纸本)9781538669488

The industry that are providing healthcare is producing a large amount of data. We know that Machine Learning algorithms can also be used to find hidden information for diagnosis and effective decision making. In recent years, Liver disorders have increased rapidly and it is considered to be a very fatal disease in many countries like - Egypt, Moldava etc. For this research paper, the main aim is to predict liver disease using different classification algorithms. The algorithms used for this purpose of work is Logistic Regression, K-Nearest Neighbour and Support Vector Machines. Accuracy score and confusion matrix is used to compare this classification algorithm.

关键词： Logistics classification algorithms Support vector machines Liver diseases Machine learning Diseases

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Multi-label classification algorithms

Comparative Analysis of Multi-label Classification Algorithm...

引用

International Conference on Secure Cyber Computing and Communication (ICSCCC)

作者： Seema Sharma Deepti Mehrotra Amity University Uttar Pradesh India

ISBN: (纸本)9781538663745;9781538663738

Multi-label classification has generated enthusiasm in many fields over the last few years. It allows the classifications of dataset where each instance can be associated with one or more label. It has successfully ended up being superiorstrategy as compared to Single labelclassification. In this paper, we provide an overview of multi-label classification approaches. We also discussed the various tools thatutilizes MLC approaches. Lastly, we have presented an experimental study to compare different algorithms of multi-label classification. After applying and studying the accuracies of various multilabel classification techniques, we have found that performance of Random Forest is better than the rest of the other compared multilabelclassification algorithms with 96% accuracy.

关键词： classification algorithms Correlation Tools Prediction algorithms Feature extraction Loss measurement

来源：评论

学校读者我要写书评

暂无评论

Comparative study of classification algorithms for damage classification in smart composite laminates

Comparative study of classification algorithms for damage cl...

引用

Conference on Nanosensors, Biosensors, Info-Tech Sensors and 3D Systems

作者： Khan, Asif Ryoo, Chang-Kyung Kim, Heung Soo Dongguk Univ Seoul Dept Mech Robot & Energy Engn 30 Pildong Ro1 Gil Seoul 04620 South Korea Inha Univ Dept Aerosp Engn 100 Inharo Incheon 22212 South Korea

ISBN: (纸本)9781510608191;9781510608207

This paper presents a comparative study of different classification algorithms for the classification of various types of inter-ply delaminations in smart composite laminates. Improved layerwise theory is used to model delamination at different interfaces along the thickness and longitudinal directions of the smart composite laminate. The input-output data obtained through surface bonded piezoelectric sensor and actuator is analyzed by the system identification algorithm to get the system parameters. The identified parameters for the healthy and delaminated structure are supplied as input data to the classification algorithms. The classification algorithms considered in this study are ZeroR, classification via regression, Naive Bayes, Multilayer Perceptron, Sequential Minimal Optimization, Multiclass-Classifier, and Decision tree (J48). The open source software of Waikato Environment for Knowledge Analysis (WEKA) is used to evaluate the classification performance of the classifiers mentioned above via 75-25 holdout and leave-one-sample-out cross-validation regarding classification accuracy, precision, recall, kappa statistic and ROC Area.

关键词： classification algorithms smart composite laminates delamination improved layerwise theory WEKA

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Different classification algorithms for Prediction of Diabetes Disease 17

Comparative Analysis of Different Classification Algorithms ...

引用

2nd International Conference on Internet of things, Data and Cloud Computing (ICC)

作者： AlThunayan, Lujain AlSahdi, Nahed Syed, Liyakathunisa Prince Sultan Univ Coll Comp & Informat Sci Dept Software Engn Riyadh Saudi Arabia Prince Sultan Univ Coll Comp & Informat Sci Dept Comp Sci Riyadh Saudi Arabia

ISBN: (纸本)9781450347747

Diabetes Mellitus is fast becoming an endemic in the world, especially in developing countries. An efficient prediction methodology is needed to diagnose the diabetes disease, which can be helpful for health care professionals. Data mining techniques have been widely used in healthcare to mine knowledgeable information from medical data. Data mining is the process of analyzing data based on different perspectives and summarizing it into useful information. Data mining techniques are proven forearly prediction of several diseases with higher accuracy and lower error rate and cost. classification is one of the generally used techniques in medical data mining. In this paper, we intend to explore various data mining techniques to show the comparison of different classification algorithms using Waikato Environment for Knowledge Analysis (WEKA) and analyze the results in order to find the best suitable classification algorithm for prediction of diabetes diseases. Various performance measures metrics such as sensitivity, specificity, accuracy and error rate are used for finding the accuracy of the classifier.

关键词： Data Mining Diabetes classification algorithms WEKA

来源：评论

学校读者我要写书评

暂无评论

Modeling and Evaluating of Decision Support System Based on Cost-Sensitive Multiclass classification algorithms

Modeling and Evaluating of Decision Support System Based on ...

引用

International Conference on Intelligent and Interactive Systems and Applications (IISA)

作者： Wu, Xiaobo Sun, Hong Wu, Zhaohui Miao, Xuna China Acad Transportat Sci Beijing 100029 Peoples R China Henan Univ Econ & Law Zhengzhou 450052 Henan Peoples R China

ISBN: (纸本)9783319495682;9783319495675

Through analyzing the limitations of modeling and evaluating the cost-sensitive multiclass classification algorithms, a series of models based on three classification algorithms are presented. On this basis, expected cost of misclassification as a cost-sensitive metric, which is introduced for evaluating the more cost details of models.

关键词： Decision support system classification algorithms Cost-sensitive evaluating

来源：评论

学校读者我要写书评

暂无评论

A Comparative Analysis of classification algorithms in Diabetic Retinopathy Screening 7

A Comparative Analysis of Classification Algorithms in Diabe...

引用

7th International Conference on Computer and Knowledge Engineering (ICCKE)

作者： Mohammadian, Saboora Karsaz, Ali Roshan, Yaser M. Khorasan Inst Higher Educ Elect Engn Dept Mashhad Iran Point Pk Univ Elect Engn Dept Pittsburgh PA 15232 USA

ISBN: (纸本)9781538608043

Automated screening of diabetic retinopathy plays an important role in diagnosis of the disease in early stages and preventing blindness in patients with diabetes. Various machine learning approaches have been studied in literature with the purpose of improving the accuracy of the screening methods. Although the performance of the machine learning algorithm depends on the application and the type of data, yet there is no comprehensive analysis of different approaches in the diabetic retinopathy screening to choose the best approach. To this end, in this study a comparative analysis of nine common classification algorithms is performed to select the most applicable approach for the specific problem of screening diabetic retinopathy patients. Individual algorithms are optimized with respect to their tunable parameters, and are compared together in terms of their accuracy, precision, recall, and F1-score. Simulation results demonstrate the difference between the performances of individual classification algorithms and can be used as a deciding factor in method selection for further research.

关键词： Diabetic retinopathy machine learning classification algorithms

来源：评论

学校读者我要写书评

暂无评论

Research on Disease classification Model and algorithms Based on Gene Expression Data

Research on Disease Classification Model and Algorithms Base...

引用

International Conference on Data Science and Business Analytics (ICDSBA)

作者： Yue Li Changyin Zhou School of Mathematics and System Science Shandong University of Science and Technology Qingdao China

ISBN: (数字)9781728146447

ISBN: (纸本)9781728146454

High dimension, small sample size of gene expression data lead a great deal of difficulty to disease classification, in-depth model and algorithm research is carried out to solve this problem. Firstly, a linear combination model of weak classifier is constructed by boosting method and the feature subset is selected by removing the zero-weight feature genes in the boosting method. Then, three classification methods, boosting method, SVM and K-nearest neighbor are integrated to learn in order to improve the accuracy of the classification model. Finally, the classification model of ensemble learning is applied in colon cancer dataset. Rather than a single classification model, ensemble method can reduce dimension of data and obtain higher accuracy shown by the experimental results.

关键词： Support vector machines Lead Data science Boosting Data models classification algorithms Gene expression

来源：评论

学校读者我要写书评

暂无评论

Determining single tuition fee of higher education in Indonesia: A comparative analysis of data mining classification algorithms

Determining single tuition fee of higher education in Indone...

引用

Conference on New Media Studies (CoNMedia)

作者： Muhammad Nur Yasir Utomo Adhistya Erna Permanasari Eddy Tungadi Irfan Syamsuddin Department of Electrical Engineering and Information Technology Universitas Gadjah Mada Yogyakarta Indonesia Computer and Network Engineering Study Program Politeknik Negeri Ujung Pandang Makassar Indonesia

ISBN: (纸本)9781509062850

Student's Single Tuition Fee or Uang Kuliah Tunggal (UKT) is a subsidy policy in higher education by the Indonesian government. This policy regulates the tuition fees incurred by each student at each semester in every higher education institutions. Since the cost of UKT expenses is influenced by the financial ability of each student, therefore the cost of education among students must be grouped into several classes. Until recently, there has been no standard to make such classification whereas such determination is an important task to solve by every higher institution in Indonesia. This study aims to compare five data mining classification algorithms (Gaussian Naïve Bayes, Multinomial Naïve Bayes, Bernoulli Naïve Bayes, Decision Tree and SVM) to find the best algorithm for the case of determining the UKT classes. The experiment is conducted using 230 training data and 10-fold cross-validation evaluation. Based on the result, Decision Tree managed to obtain average accuracy value of 0.814 or 81.4%. Finally, Decision Tree is used to classify the UKT classes of3258 data of students.

关键词： classification algorithms Data mining Decision trees Support vector machines Economics Niobium Education

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 << < 14 15 16 17 18 19 20 21 22 23 > >>

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：