L2-Regularized Logistic Regression Algorithm
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An L2-Regularized Logistic Regression Algorithm is a regularized logistic regression algorithm that uses L2 Regularization.
- Context:
- It can suppresses model over-fitting.
- It can add minimal complexity to existing problems and therefore be fast to calculate.
- …
- Counter-Example(s):
- See: Rotationally Invariant Algorithm.
References
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