Bias Term

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.

A theoretical framework analyzing what classes of functions can be learned, how efficiently, and with what guarantees.

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.