L1-Regularized Logistic Regression Algorithm

An L1-Regularized Logistic Regression Algorithm is a Logistic Regression Algorithm that uses L1-norm regularization.

• Counter-Example(s):
  • L2-Regularized Logistic Regression Algorithm.
• See: L1-Norm.

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References

2008

• (Murphy, 2008) ⇒ Kevin P. Murphy. (2008). “L1 Regularization." CS540 Machine learning, Lecture 13.

2006

• (Lee et al., 2006) ⇒ Su-In Lee, Honglak Lee, Pieter Abbeel, and Andrew Y. Ng. (2006). “Efficient L1 Regularized Logistic Regression.” In: Proceedings of the 2006 AAAI Conference (AAAI 2006).

2004

• (Ng, 2004) ⇒ Andrew Y. Ng. (2004). “Feature Selection, L1 vs. L2 Regularization, and Rotational Invariance.” In: Proceedings of the twenty-first International Conference on Machine learning (ICML 2004) doi:10.1145/1015330.1015435

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