VC Dimension

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

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 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...