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Data science using Oracle Data Miner and Oracle R Enterprise [electronic resource] : transform your business systems into an analytical powerhouse

Data science using Oracle Data Miner and Oracle R Enterprise [electronic resource] : transform your business systems into an analytical powerhouse

자료유형
E-Book(소장)
개인저자
Das, Sibanjan.
서명 / 저자사항
Data science using Oracle Data Miner and Oracle R Enterprise [electronic resource] : transform your business systems into an analytical powerhouse / Sibanjan Das.
발행사항
Berkeley, CA :   Apress,   c2016.  
형태사항
1 online resource (xxii, 289 p.) : ill. (some col.).
ISBN
9781484226148 (e-book) 9781484226131
요약
Automate the predictive analytics process using Oracle Data Miner and Oracle R Enterprise. This book talks about how both these technologies can provide a framework for in-database predictive analytics. You'll see a unified architecture and embedded workflow to automate various analytics steps such as data preprocessing, model creation, and storing final model output to tables. You'll take a deep dive into various statistical models commonly used in businesses and how they can be automated for predictive analytics using various SQL, PLSQL, ORE, ODM, and native R packages. You'll get to know various options available in the ODM workflow for driving automation. Also, you'll get an understanding of various ways to integrate ODM packages, ORE, and native R packages using PLSQL for automating the processes.
일반주기
Title from e-Book title page.  
내용주기
Introduction Chapter 1 : Getting Started with Oracle Advanced Analytics -- Chapter 2 : Installation and Hello World -- Chapter 3: Clustering Methods -- Chapter 4: Association Rules -- Chapter 5: Regression Analysis -- Chapter 6: Classification Techniques -- Chapter 7: Advanced Topics -- Chapter 8: Solution Deployment.
서지주기
Includes bibliographical references and index.
이용가능한 다른형태자료
Issued also as a book.  
일반주제명
Data mining. Computer science. Programming languages (Electronic computers). Database management.
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020 ▼a 9781484226148 (e-book)
020 ▼a 9781484226131
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082 0 4 ▼a 006.312 ▼2 23
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100 1 ▼a Das, Sibanjan.
245 1 0 ▼a Data science using Oracle Data Miner and Oracle R Enterprise ▼h [electronic resource] : ▼b transform your business systems into an analytical powerhouse / ▼c Sibanjan Das.
260 ▼a Berkeley, CA : ▼b Apress, ▼c c2016.
300 ▼a 1 online resource (xxii, 289 p.) : ▼b ill. (some col.).
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references and index.
505 0 ▼a Introduction Chapter 1 : Getting Started with Oracle Advanced Analytics -- Chapter 2 : Installation and Hello World -- Chapter 3: Clustering Methods -- Chapter 4: Association Rules -- Chapter 5: Regression Analysis -- Chapter 6: Classification Techniques -- Chapter 7: Advanced Topics -- Chapter 8: Solution Deployment.
520 ▼a Automate the predictive analytics process using Oracle Data Miner and Oracle R Enterprise. This book talks about how both these technologies can provide a framework for in-database predictive analytics. You'll see a unified architecture and embedded workflow to automate various analytics steps such as data preprocessing, model creation, and storing final model output to tables. You'll take a deep dive into various statistical models commonly used in businesses and how they can be automated for predictive analytics using various SQL, PLSQL, ORE, ODM, and native R packages. You'll get to know various options available in the ODM workflow for driving automation. Also, you'll get an understanding of various ways to integrate ODM packages, ORE, and native R packages using PLSQL for automating the processes.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Data mining.
650 0 ▼a Computer science.
650 0 ▼a Programming languages (Electronic computers).
650 0 ▼a Database management.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-1-4842-2614-8
945 ▼a KLPA
991 ▼a E-Book(소장)

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/e-Book 컬렉션/ 청구기호 CR 006.312 등록번호 E14019627 도서상태 대출불가(열람가능) 반납예정일 예약 서비스 M

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