Name
Abstract | ||
|---|---|---|
Stochastically searching the space of candidate clauses is an appealing way to scale up ILP to large datasets. We address an approach that uses a Bayesian network model to adaptively guide search in this space. We examine guiding search towards areas that previously performed well and towards areas that ILP has not yet thoroughly explored. We show improvement in area under the curve for recall-precision curves using these modifications. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-78469-2_20 | ILP |
Keywords | Field | DocType |
recall-precision curve,inductive logic programming,large datasets,bayesian network model,guide search,candidate clause,guiding search,stochastic search,area under the curve,bayesian network | Inductive logic programming,Computer science,Bayesian network,Artificial intelligence,Machine learning | Conference |
Volume | ISSN | ISBN |
4894 | 0302-9743 | 3-540-78468-3 |
Citations | PageRank | References |
2 | 0.37 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Louis Oliphant | 1 | 43 | 3.44 |
| Jude W. Shavlik | 2 | 3057 | 619.89 |