Cross-Entropy

A function measuring prediction error (and sometimes calibration), guiding gradient-based optimization.

Measures how one probability distribution diverges from another.

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.

Systematic error introduced by simplifying assumptions in a learning algorithm.

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.