L2-Regularized Logistic Regression Algorithm

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):
  • a L1-Regularized Logistic Regression Algorithm.
• 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

---