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Learning interactions via hierarchical group-lasso regularization
We introduce a method for learning pairwise interactions in a linear regression or logistic regression model in a manner that satisfies strong hierarchy: whenever an interaction is estimated to be nonzero, both its associated main effects are also included in the model. We motivate our approach by m...
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| Publicado no: | J Comput Graph Stat |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2015
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4706754/ https://ncbi.nlm.nih.gov/pubmed/26759522 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/10618600.2014.938812 |
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