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Update bess_base.py
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Mamba413 committed May 6, 2024
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13 changes: 7 additions & 6 deletions python/abess/bess_base.py
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Expand Up @@ -51,8 +51,8 @@ class bess_base(BaseEstimator):
The full name of each option:
- 'aic': Akaike information criterion
- 'bic': Bayesian information criterion
- 'gic': Generalized information criterion. It refers to "special information criterion" in Zhu, Junxian, et al. "A polynomial algorithm for best-subset selection problem." Proceedings of the National Academy of Sciences (2020).
- 'ebic': Extended Bayesian information criterion
- 'gic': Generalized information criterion (see [2-4]). It refers to "special information criterion" in [1].
- 'ebic': Extended Bayesian information criterion [5]
- 'loss': Loss value
ic_coef : float, optional, default=1.0
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References
----------
- Junxian Zhu, Canhong Wen, Jin Zhu, Heping Zhang, and Xueqin Wang.
A polynomial algorithm for best-subset selection problem.
Proceedings of the National Academy of Sciences,
117(52):33117-33123, 2020.
- [1] Zhu, J., Wen, C., Zhu, J., Zhang, H., & Wang, X. (2020). A polynomial algorithm for best-subset selection problem. Proceedings of the National Academy of Sciences, 117(52), 33117-33123.
- [2] Tang, B., Zhu, J., Zhu, J., Wang, X., & Zhang, H. (2023). A Consistent and Scalable Algorithm for Best Subset Selection in Single Index Models. arXiv preprint arXiv:2309.06230.
- [3] Zhu, J., Zhu, J., Tang, B., Chen, X., Lin, H., & Wang, X. (2023). Best-subset selection in generalized linear models: A fast and consistent algorithm via splicing technique. arXiv preprint arXiv:2308.00251.
- [4] Zhang, Y., Zhu, J., Zhu, J., & Wang, X. (2023). A splicing approach to best subset of groups selection. INFORMS Journal on Computing, 35(1), 104-119.
- [5] Chen, J., & Chen, Z. (2008). Extended Bayesian information criteria for model selection with large model spaces. Biometrika, 95(3), 759-771.
"""

# attributes
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