Summary

• Logistic regression: classification tasks

• Robust logistic regression: helps with misclassification outliers

• Bayesian logistic regression:

  • pro: helps measure uncertainty
  • con: computationally expensive

• Probit approximation:

  • pro: computationally inexpensive
  • con: loses info about posterior distribution