KL Divergence

Quantifies shared information between random variables.

Measures how much information an observable random variable carries about unknown parameters.

Estimating parameters by maximizing likelihood of observed data.

Updating beliefs about parameters using observed evidence and prior distributions.

Error due to sensitivity to fluctuations in the training dataset.

Reduction in uncertainty achieved by observing a variable; used in decision trees and active learning.

A measure of randomness or uncertainty in a probability distribution.

Measures divergence between true and predicted probability distributions.