Package: RODM
Version: 1.0
Date: 2010-05-01
Title: R interface to Oracle Data Mining
Author: Pablo Tamayo <pablo.tamayo@oracle.com> and Ari Mozes
<ari.mozes@oracle.com>
Maintainer: Pablo Tamayo <pablo.tamayo@oracle.com>
Depends: R (>= 2.10.1), RODBC
Suggests: RODBC, mlbench, verification, PASWR, scatterplot3d
Description: 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).
License: GPL (>= 2)
URL: http://www.r-project.org
Packaged: 2010-05-26 17:38:56 UTC; Tamayo
Repository: CRAN
Date/Publication: 2010-05-26 19:58:47

Package: RODM
Version: 1.1
Date: 2011-11-20
Title: R interface to Oracle Data Mining
Author: Pablo Tamayo <pablo.tamayo@oracle.com> and Ari Mozes
<ari.mozes@oracle.com>
Maintainer: Pablo Tamayo <pablo.tamayo@oracle.com>
Depends: R (>= 2.10.1), RODBC
Suggests: RODBC, mlbench, verification, PASWR, scatterplot3d
Description: 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).
License: LGPL (>= 2)
URL: http://www.r-project.org
Packaged: 2012-10-29 08:57:32 UTC; ripley
Repository: CRAN
Date/Publication: 2012-10-29 08:57:32