Sunday, March 23, 2014

Using the in-database ODM algorithms in ORE

Oracle R Enterprise is the version of R that Oracle has that runs in the database instead of on your laptop or desktop.

Oracle already has a significant number of data mining algorithms in the database. With ORE they have exposed these so that they can be easily called from your R (ORE) scripts.

To access these in-database data mining algorithms you will need to use the ore.odm package.

ORE is continually being developed with new functionality being added all the time. Over the past 2 years Oracle have released and updated version of ORE about every 6 months. ORE is generally not certified with the latest version of R. But is slightly behind but only a point or two of the current release. For example the current version of ORE 1.4 (released only last week) is certified for R version 3.0.1. But the current release of R is 3.0.3.

Will ORE work with the latest version of R? The simple answer is maybe or in theory it should, but is not certified.

Let's get back to ore.dm. The following table maps the ore.odm functions to the in-database Oracle Data Mining functions.

ORE Function Oracle Data Mining Algorithm What Algorithm can be used for
ore.odmAI Minimum Description Length Attribute Importance
ore.odmAssocRules Apriori Association Rules
ore.odmDT Decision Tree Classification
ore.odmGLM Generalized Linear Model Classification and Regression
ore.odmKMeans k-Means Clustering
ore.odmNB Naïve Bayes Classification
ore.odmNMF Non-Negative Matrix Factorization Feature Extraction
ore.odmOC O-Cluster Clustering
ore.odmSVM Support Vector Machines Classification and Regression

As you can see we only have a subset of the in-database Oracle Dat Miner algorithms. This is a pity really, but I'm sure as we get newer releases of ORE these will be added.

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