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- Anomaly and Fraud Detection with Oracle Data Mining 11G Release 2
- Oracle Data Mining Concepts, 10G Release 2 (10.2)
- Oracle Data Mining
- Oracle Data Miner (Extension of SQL Developer 4.0) Integrate Oracle R Enterprise Mining Algorithms Into a Workflow Using the SQL Query Node
- Oracle Advanced Analytics Option
- Oracle Machine Learning/Predictive Analtyics • Traditional— “Move the Data” —“Don’T Move the Data!”
- Oracle In-Database Analytics
- Learning R Series Session 1: Introduction to Oracle's R Technologies and Oracle R Enterprise 1.3 Mark Hornick, Senior Manager, Development Oracle Advanced Analytics
- Oracle Data Mining Application Developer's Guide, 11G Release 2 (11.2) E12218-07
- Oracle Data Mining Application Developer's
- Oracle R Enterprise User's Guide, Release 1.3 for Windows, Linux, Solaris, and AIX E36761-08
- Oracle Data Mining
- Oracle® Data Mining Concepts
- Factoring Nonnegative Matrices with Linear Programs
- Oracle® Data Mining Concepts 12C Release 1 (12.1) E17692-19
- Data-Mining-Api-Guide.Pdf
- OLAP Using Student's Result Analysis
- Oracle Data Mining 11G Release 2 Competing on In-Database Analytics
- Predictive Analytics! 3
- Oracle® Data Mining Tutorial for Oracle Data Mining 10G Release 2 Oracle Data Mining 11G Release 1
- Oracle Data Mining Administrator's Guide, 11G Release 1 (11.1) B28130-03
- Oracle Machine Learning and Advanced Analytics Report
- Oracle Data Sheet
- Integrating Association Rules with Decision Trees in Object
- Oracle Data Mining Topics
- Oracle Data Mining Administrator's Guide, 11G Release 2 (11.2) E16807-08
- Oracle9i Data Mining Concepts, Release 9.2.0.2
- Fraud and Anomaly Detection Using Oracle Advanced Analytic Option 12C
- Oracle® Data Mining Concepts
- White Paper | July 2019