What are advanced calibration techniques in machine learning?

What are advanced calibration techniques in machine learning?

Advanced calibration techniques are methods used to improve the accuracy of probabilistic predictions in machine learning models.

Can you explain some specific techniques?

Sure! Techniques like Platt Scaling, Isotonic Regression, and Beta Calibration are commonly used for this purpose.

How do these techniques differ from each other?

Platt Scaling uses a logistic regression model, Isotonic Regression is non-parametric, and Beta Calibration models the probabilities using a beta distribution.

When should I use each technique?

Use Platt Scaling for binary classification, Isotonic Regression when you have enough data, and Beta Calibration for more complex distributions.