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the texbook下载
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2020-03-14 03:30:11
这是著名计算机科学家knuth开发的tex科学排版系统的详细使用说明书.
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//download.csdn.net/download/libl05/1578779?utm_source=bbsseo
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the texbook下载
这是著名计算机科学家knuth开发的tex科学排版系统的详细使用说明书. 相关下载链接://download.csdn.net/download/libl05/1578779?utm_source=bbsseo
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Data Mining: The
Tex
t
book
(Springer 2015原版超清)
This
tex
t
book
explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues. It goes beyond the traditional focus on data mining problems to introduce advanced data types such as
tex
t, time series, discrete sequences, spatial data, graph data, and social networks. Until now, no single
book
has addressed all these topics in a comprehensive and integrated way. The chapters of this
book
fall into one of three categories: Fundamental chapters: Data mining has four main problems, which correspond to clustering, classification, association pattern mining, and outlier analysis. These chapters comprehensively discuss a wide variety of methods for these problems. Domain chapters: These chapters discuss the specific methods used for different domains of data such as
tex
t data, time-series data, sequence data, graph data, and spatial data. Application chapters: These chapters study important applications such as stream mining, Web mining, ranking, recommendations, social networks, and privacy preservation. The domain chapters also have an applied flavor.
Data Mining: The
Tex
t
book
(Springer 原版超清)
Data Mining: The
Tex
t
book
By 作者: Charu C. Aggarwal ISBN-10 书号: 3319141414 ISBN-13 书号: 9783319141411 Edition 版本: 2015 出版日期: 2015-04-14 pages 页数: (734 ) $89.99 This
tex
t
book
explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues. It goes beyond the traditional focus on data mining problems to introduce advanced data types such as
tex
t, time series, discrete sequences, spatial data, graph data, and social networks. Until now, no single
book
has addressed all these topics in a comprehensive and integrated way. The chapters of this
book
fall into one of three categories: Fundamental chapters: Data mining has four main problems, which correspond to clustering, classification, association pattern mining, and outlier analysis. These chapters comprehensively discuss a wide variety of methods for these problems. Domain chapters: These chapters discuss the specific methods used for different domains of data such as
tex
t data, time-series data, sequence data, graph data, and spatial data. Application chapters: These chapters study important applications such as stream mining, Web mining, ranking, recommendations, social networks, and privacy preservation. The domain chapters also have an applied flavor. Appropriate for both introductory and advanced data mining courses, Data Mining: The
Tex
t
book
balances mathematical details and intuition. It contains the necessary mathematical details for professors and researchers, but it is presented in a simple and intuitive style to improve accessibility for students and industrial practitioners (including those with a limited mathematical background). Numerous illustrations, examples, and exercises are included, with an emphasis on semantically interpretable examples.
Data Mining The
Tex
t
book
这是关于数据挖掘的电子书,高清,最新版本,经典著作,英文版
Linux教程(LINUX THE
TEX
T
BOOK
) 2/2
Linux教程(LINUX THE
TEX
T
BOOK
) 2/2
Linux教程(LINUX THE
TEX
T
BOOK
) 1/2
Linux教程(LINUX THE
TEX
T
BOOK
) 1/2
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