Oracle Data Mining Algorithms

Two major categories:

- Supervised learning
- Unsupervised learning

Supervised learning requires the data analyst to identify a target attribute (dependent variable). The supervised-learning technique then sifts through data trying to find patterns and relationships between the independent attributes (predictors) and the dependent attribute (target attribute).

In unsupervised learning, the user does not specify a target attribute for the data mining algorithm. 

Unsupervised learning techniques such as Associations and Clustering make no assumptions about a target attribute. Instead, they allow the data mining algorithm to finds associations and clusters in the data independent of any defined business objective.