國立虎尾科技大學 |

Data Science Using Oracle Data Miner and Oracle R Enterprise = transform your business systems into an analytical powerhouse /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Data Science Using Oracle Data Miner and Oracle R Enterprise/ by Sibanjan Das.
Reminder of title:	transform your business systems into an analytical powerhouse /
Author:	Das, Sibanjan.
Published:	Berkeley, CA :Apress : : 2016.,
Description:	xxii, 289 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Data mining. -
Online resource:	http://dx.doi.org/10.1007/978-1-4842-2614-8
ISBN:	9781484226148$q(electronic bk.)

Data Science Using Oracle Data Miner and Oracle R Enterprise = transform your business systems into an analytical powerhouse /
Das, Sibanjan.

Data Science Using Oracle Data Miner and Oracle R Enterprisetransform your business systems into an analytical powerhouse /[electronic resource] :by Sibanjan Das. - Berkeley, CA :Apress :2016. - xxii, 289 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9781484226148$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-2614-8doiSubjects--Topical Terms:

528622
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Data Science Using Oracle Data Miner and Oracle R Enterprise = transform your business systems into an analytical powerhouse /
LDR:02098nam a2200289 a 4500 001 868819
003 DE-He213
005 20161223031143.0
006 m d
007 cr nn 008maaau
008 170720s2016 cau s 0 eng d
020 $a 9781484226148$q(electronic bk.)
020 $a 9781484226131$q(paper)
024 7 $a 10.1007/978-1-4842-2614-8 $2 doi
035 $a 978-1-4842-2614-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D343
082 0 4 $a 006.312 $2 23
090 $a QA76.9.D343 $b D229 2016
100 1 $a Das, Sibanjan. $3 1116657
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 by Sibanjan Das.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2016.
300 $a xxii, 289 p. : $b ill., digital ; $c 24 cm.
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.
650 0 $a Data mining. $3 528622
650 0 $a Computer science. $3 573171
650 0 $a Programming languages (Electronic computers) $3 596941
650 0 $a Database management. $3 557799
650 1 4 $a Computer Science. $3 593922
650 2 4 $a Big Data. $3 1017136
650 2 4 $a Database Management. $3 669820
650 2 4 $a Programming Languages, Compilers, Interpreters. $3 669782
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-1-4842-2614-8
950 $a Professional and Applied Computing (Springer-12059)