Variance Term

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.

Measures how one probability distribution diverges from another.

A model is PAC-learnable if it can, with high probability, learn an approximately correct hypothesis from finite samp...

A measure of a model class’s expressive capacity based on its ability to shatter datasets.

Measures a model’s ability to fit random noise; used to bound generalization error.

Systematic error introduced by simplifying assumptions in a learning algorithm.