Causal Feature Selection with Dimension Reduction for Interpretable Text Classification
| dc.contributor.author | Shan, Guohou | |
| dc.contributor.author | Foulds, James | |
| dc.contributor.author | Pan, Shimei | |
| dc.date.accessioned | 2020-12-09T17:11:04Z | |
| dc.date.available | 2020-12-09T17:11:04Z | |
| dc.date.issued | 2020-10-09 | |
| dc.description.abstract | Text features that are correlated with class labels, but do not directly cause them, are sometimesuseful for prediction, but they may not be insightful. As an alternative to traditional correlation-basedfeature selection, causal inference could reveal more principled, meaningful relationships betweentext features and labels. To help researchers gain insight into text data, e.g. for social scienceapplications, in this paper we investigate a class of matching-based causal inference methods fortext feature selection. Features used in document classification are often high dimensional, howeverexisting causal feature selection methods use Propensity Score Matching (PSM) which is known to beless effective in high-dimensional spaces. We propose a new causal feature selection framework thatcombines dimension reduction with causal inference to improve text feature selection. Experiments onboth synthetic and real-world data demonstrate the promise of our methods in improving classificationand enhancing interpretability. | en_US |
| dc.description.uri | https://arxiv.org/abs/2010.04609 | en_US |
| dc.format.extent | 11 pages | en_US |
| dc.genre | journal articles preprints | en_US |
| dc.identifier | doi:10.13016/m2wrpa-ctie | |
| dc.identifier.citation | Guohou Shan, James Foulds and Shimei Pan, Causal Feature Selection with Dimension Reduction for Interpretable Text Classification, https://arxiv.org/abs/2010.04609 | en_US |
| dc.identifier.uri | http://hdl.handle.net/11603/20210 | |
| dc.language.iso | en_US | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Information Systems Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
| dc.rights | Access to this item will begin on 4/30/21 | |
| dc.title | Causal Feature Selection with Dimension Reduction for Interpretable Text Classification | en_US |
| dc.type | Text | en_US |