The relational data model has simple and clear foundations on which significant 
theoretical and systems research has flourished. By contrast, most research on data 
mining has focused on algorithmic issues. A major open question is ``what's an 
appropriate foundation for data mining, which can accommodate disparate mining 
tasks.'' We address this problem by presenting a database model and an algebra for 
data mining. The database model is based on the 3W-model introduced 
by~\citeN{JLN00}. This model relied on black box mining operators. A main 
contribution of this paper is to open up these black boxes, by using generic 
operators in a data mining algebra. Two key operators in this algebra are 
regionize, which creates regions (or models) from data tuples, and a restricted 
form of looping called mining loop. Then, the resulting data mining algebra is 
studied and properties concerning expressive power and complexity are established. 
We present results in three directions: (1) expressiveness of the mining algebra; 
(2) relations with alternative frameworks, and (3) interactions between regionize 
and mining loop.