By Sibanjan Das
Automate the predictive analytics technique utilizing Oracle info Miner and Oracle R company. This publication talks approximately how either those applied sciences delivers a framework for in-database predictive analytics. you will see a unified structure and embedded workflow to automate a variety of analytics steps equivalent to facts preprocessing, version construction, and storing ultimate version output to tables.
You'll take a deep dive into a variety of statistical versions normal in companies and the way they are often computerized for predictive analytics utilizing a variety of SQL, PLSQL, ORE, ODM, and local R programs. you will get to understand a number of ideas on hand within the ODM workflow for using automation. additionally, you will get an realizing of assorted how one can combine ODM programs, ORE, and local R programs utilizing PLSQL for automating the processes.
Data technology Automation utilizing Oracle Data Miner and Oracle R Enterprise starts off with an advent to company analytics, overlaying why automation is critical and the extent of complexity in automation at each one analytic level. Then, it specializes in how predictive analytics will be computerized through the use of Oracle facts Miner and Oracle R firm. additionally, it explains while and why ODM and ORE are for use jointly for automation.
The next chapters element quite a few statistical methods used for predictive analytics equivalent to calculating characteristic value, clustering equipment, regression research, category thoughts, ensemble types, and neural networks. In those chapters additionally, you will get to appreciate the automation strategies for every of those statistical procedures utilizing ODM and ORE in addition to their program in a real-life enterprise use case.
What you are going to learn
- Discover the performance of Oracle info Miner and Oracle R Enterprise
- Gain ways to practice in-database predictive analytics
- Use Oracle's SQL and PLSQL APIs for construction analytical solutions
- Acquire wisdom of universal and widely-used company statistical research techniques
Who this e-book is for
- IT executives, BI architects, Oracle architects and builders, R clients and statisticians.
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Additional resources for Data Science Using Oracle Data Miner and Oracle R Enterprise: Transform Your Business Systems into an Analytical Powerhouse
Sibanjan Das 2016 S. 2) Enterprise Edition/ Oracle 11 Enterprise Edition should be already installed. If not installed, it can be downloaded and installed from Oracle Technology Network Database Download page. 3) is installed. If not, it can be downloaded and installed from Oracle Technology Network SQL Developer Download Page. • Validate whether the Data Miner option is already enabled. This can be done by checking if DATA_MINING option is set to TRUE in the table V$Option. If it is FALSE, ask your DBA (database administrator) to enable the data mining option or enable it running command chopt enable dm from the installed Oracle Database’s home bin directory.
Figure 2-12. Select Connection screen 13. Once a user is selected, it appears in the connections tab as shown in Figure 2-13. 45 Chapter 2 ■ Installation and Hello World Figure 2-13. Data Miner DMUSER connection 14. Select the plus (+) icon beside DMUSER, which will pop up a notification to install the Data Miner repository (Figure 2-14). Click Yes to continue Figure 2-14. Install the Data Miner repository 15. As SYS user has SYSDBA credentials, it can be used to install a data mining user. Enter the SYS credentials and continue with the installation (see Figure 2-15).
Table 1-7. Routines in the ORE Package ORE Package Utility OREbase The base package for ORE. Contains methods to convert an object to an ORE object, create constants, database connection functions, and many more OREstats Provide methods for statistical tests OREgraphics Provide methods for visualization through graphs and plot OREeda An exploratory data analysis package that provides various methods for univariate analysis (analyzing a single variable at a time), calculating correlations, summarizing data, ranking values, and many more OREdm Exposes proprietary Oracle Data Mining algorithms; this forms a base to integrate the Oracle Data Miner’s algorithms to Oracle R Enterprise OREpredict Contains functions for generating and scoring model predictions for data present in the oracle database using R models ORExml Supports XML translation between R and the oracle database Apart from these packages, Oracle R Enterprise supports various other open source R packages such as arules, Cairo, DBI, png (Portable Network Graphics), ROracle, statmod, and randomforest.