Scalable holistic linear regression
We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting algorithm scales with the num...
| Main Authors: | , |
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| Other Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Elsevier BV,
2021-03-29T16:15:10Z.
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| Subjects: | |
| Online Access: | Get fulltext |