Functional Dependency Inference Problem
The functional dependency inference problem is to find a cover for the set of functional dependencies that hold in a given relation. A functional dependency (abbr. FD), , is a statement where and are sets of attributes. If is a relation on a set of attributes that contains and , then obeys the FD if every two tuples of which have the same projection on also have the same projection on . Given , we say that is a functional dependency from to , that is functionally dependent on or that functionally determines . From the definition it follows that for each pair of sets and there is at most one functional dependency from to . Therefore, we usually omit the name of the FD and write .
Parameters
- : number of attributes
- : number of tuples/rows/data points
Filters
Computational Model
Randomization
Approximation
Algorithms Table
Displaying 2 of 2 algorithms
| See more | ||||
|---|---|---|---|---|
| Schlimmer | 1993 | |||
| Brute force algorithm | 1967 |
Reductions Table
Insuffient Data to display table
Other relevant algorithms
Insuffient Data to display table