4.2.1.1 OML4SQL Models Supported by OML4R

The functions in the OREdm package provide access to the Oracle Machine Learning for SQL in-database machine learning functionality of Oracle Database. You use these functions to build OML4SQL models in the database.

The following table lists the OML4R functions that build OML4SQL models and the corresponding OML4SQL algorithms and functions.

Table 4-2 Oracle Machine Learning for R Model Functions

OML4R Function	OML4SQL Algorithm	OML4SQL Function
ore.odmAI	Minimum Description Length	Attribute importance for classification or regression
ore.odmAssocRules	Apriori	Association rules
ore.odmDT	Decision Tree	Classification
ore.odmEM (12.2 feature)	Expectation Maximization	Clustering
ore.odmESA (12.2 feature)	Explicit Semantic Analysis	Feature extraction
ore.odmGLM	Generalized Linear Models	Classification and regression
ore.odmKMeans	k-Means	Clustering
ore.odmNB	Naive Bayes	Classification
ore.odmNMF	Non-Negative Matrix Factorization	Feature extraction
ore.odmOC	Orthogonal Partitioning Cluster (O-Cluster)	Clustering
ore.odmRAlg (12.2 feature)	Extensible R Algorithm	Association rules, attribute importance, classification, clustering, feature extraction, and regression
ore.odmSVD (12.2 feature)	Singular Value Decomposition	Feature extraction
ore.odmSVM	Support Vector Machines	Classification and regression