R interface to Oracle Data Mining

This package implements an interface to Oracle Data Mining (ODM). It provides an ideal environment for rapid development of demos and proof of concept data mining studies. It facilitates the prototyping of vertical applications and makes ODM and the RDBMS environment easily accessible to statisticians and data analysts familiar with R but not fluent in SQL or familiar with the database environment. It also facilitates the benchmarking and testing of ODM functionality including the production of summary statistics, performance metrics and graphics. It enables the scripting and control of production data mining methodologies from a high-level environment. Oracle Data Mining (ODM) is an option of Oracle Relational Database Management System (RDBMS) Enterprise Edition (EE). It contains several data mining and data analysis algorithms for classification, prediction, regression, clustering, associations, feature selection, anomaly detection, feature extraction, and specialized analytics. It provides means for the creation, management and operational deployment of data mining models inside the database environment. For more information consult the entry for "Oracle Data Mining" in Wikipedia (en.wikipedia.org).


Reference manual

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1.1 by Pablo Tamayo, 9 years ago


Browse source code at https://github.com/cran/RODM

Authors: Pablo Tamayo <[email protected]> and Ari Mozes <[email protected]>

Documentation:   PDF Manual  

LGPL (>= 2) license

Depends on RODBC

Suggests RODBC, mlbench, verification, PASWR, scatterplot3d

See at CRAN