東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Open source software for statistical...

Segall, Richard, (1949-)

FindBook

Google Book

Amazon

博客來

Open source software for statistical analysis of big data = emerging research and opportunities /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Open source software for statistical analysis of big data/ Richard S. Segall and Gao Niu, editors.
其他題名:	emerging research and opportunities /
其他作者:	Segall, Richard,
出版者:	Hershey, Pennsylvania :IGI Global, : 2020.,
面頁冊數:	1 online resource (xiv, 237 p.)
內容註:	Chapter 1. What is open source software (OSS) and what is big data? -- Chapter 2. Open source software (OSS) for big data -- Chapter 3. Introduction to the popular open source statistical software (OSSS) -- Chapter 4. Cluster analysis in R with big data applications -- Chapter 5. Generalized linear model for automobile fatality rate prediction in R -- Chapter 6. Introduction to python and its statistical applications -- Chapter 7. A comparison of machine learning algorithms of big data for time series forecasting using python.
標題:	Statistics - Data processing. -
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-2768-9
ISBN:	9781799827702 (ebk.)

Open source software for statistical analysis of big data = emerging research and opportunities /
Open source software for statistical analysis of big dataemerging research and opportunities /[electronic resource] :Richard S. Segall and Gao Niu, editors. - Hershey, Pennsylvania :IGI Global,2020. - 1 online resource (xiv, 237 p.)

Includes bibliographical references and index.

Chapter 1. What is open source software (OSS) and what is big data? -- Chapter 2. Open source software (OSS) for big data -- Chapter 3. Introduction to the popular open source statistical software (OSSS) -- Chapter 4. Cluster analysis in R with big data applications -- Chapter 5. Generalized linear model for automobile fatality rate prediction in R -- Chapter 6. Introduction to python and its statistical applications -- Chapter 7. A comparison of machine learning algorithms of big data for time series forecasting using python.

"This book explores topics in the field of open source software for big data"--

ISBN: 9781799827702 (ebk.)Subjects--Topical Terms:

535534
Statistics
--Data processing.

LC Class. No.: QA276.4 / .O64 2020

Dewey Class. No.: 005.7

Open source software for statistical analysis of big data = emerging research and opportunities /
LDR:01570nmm a2200265 a 4500 001 2246919
003 IGIG
005 19991022112001.0
006 m o d
007 cr cn
008 211227s2020 pau fob 001 0 eng d
020 $a 9781799827702 (ebk.)
020 $a 9781799827689 (hbk.)
020 $a 9781799827696 (pbk.)
035 $a (OCoLC)1123182190
035 $a 1101012275
040 $a CaBNVSL $b eng $c CaBNVSL $d CaBNVSL
050 0 0 $a QA276.4 $b .O64 2020
082 0 0 $a 005.7 $2 23
245 0 0 $a Open source software for statistical analysis of big data $h [electronic resource] : $b emerging research and opportunities / $c Richard S. Segall and Gao Niu, editors.
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2020.
300 $a 1 online resource (xiv, 237 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. What is open source software (OSS) and what is big data? -- Chapter 2. Open source software (OSS) for big data -- Chapter 3. Introduction to the popular open source statistical software (OSSS) -- Chapter 4. Cluster analysis in R with big data applications -- Chapter 5. Generalized linear model for automobile fatality rate prediction in R -- Chapter 6. Introduction to python and its statistical applications -- Chapter 7. A comparison of machine learning algorithms of big data for time series forecasting using python.
520 3 $a "This book explores topics in the field of open source software for big data"-- $c Provided by publisher.
650 0 $a Statistics $x Data processing. $3 535534
650 0 $a Open source software. $3 581998
650 0 $a Big data. $3 2045508
700 1 $a Segall, Richard, $d 1949- $e editor. $3 3311040
700 1 $a Niu, Gao, $d 1987- $e editor. $3 3510740
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-2768-9