View Learning for Statistical Relational Learning: With an Application to Mammography
Abstract
Statistical relational learning (SRL) constructs probabilistic models from relational databases. A key capability of SRL is the learning of arcs (in the Bayes net sense) connecting entries in different rows of a relational table, or in different tables. Nevertheless, SRL approaches currently are constrained to use the existing database schema. For many database applications, users find it profitable to define alternative views of the database, in effect defining new fields or tables. Such new fields or tables can also be highly useful in learning. We provide SRL with the capability of learning new views.
Cite
Text
Davis et al. "View Learning for Statistical Relational Learning: With an Application to Mammography." International Joint Conference on Artificial Intelligence, 2005.Markdown
[Davis et al. "View Learning for Statistical Relational Learning: With an Application to Mammography." International Joint Conference on Artificial Intelligence, 2005.](https://mlanthology.org/ijcai/2005/davis2005ijcai-view/)BibTeX
@inproceedings{davis2005ijcai-view,
title = {{View Learning for Statistical Relational Learning: With an Application to Mammography}},
author = {Davis, Jesse and Burnside, Elizabeth S. and de Castro Dutra, Inês and Page, David and Ramakrishnan, Raghu and Costa, Vítor Santos and Shavlik, Jude W.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2005},
pages = {677-683},
url = {https://mlanthology.org/ijcai/2005/davis2005ijcai-view/}
}