Efficient relational learning from sparse data
| Authors | |
|---|---|
| Year of publication | 2002 |
| Type | Article in Proceedings |
| Conference | Proceedings of AIMSA'02 Conference |
| MU Faculty or unit | |
| Citation | |
| Field | Computer hardware and software |
| Keywords | relational learning; database schema redesign; mining in spatial dat |
| Description | This work deals with inductive inference of logic programs -relational learning - from examples. The work is, in the first place, application-oriented. It aims at building an easy-to-use relational learner and it focuses on the tasks that are solvable with the tool. Assumption-based learning, the new learning paradigm is introduced and the ABL system WiM is described. A methodology for experimental evaluation of ILP systems is introduced and experiments with WiM are displayed. Two classes of application -- database schema redesign and mining in spatial data - that have been successfully solved with WiM are described. |
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