Statistical classification | Computational learning theory | Measures of complexity

Natarajan dimension

In the theory of Probably Approximately Correct Machine Learning, the dimension characterizes the complexity of learning a set of functions, generalizing from the Vapnik-Chervonenkis dimension for boolean functions to multi-class functions. Originally introduced as the Generalized Dimension by Natarajan, it was subsequently renamed the Natarajan Dimension by Haussler and Long. (Wikipedia).

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Related pages

Vapnik–Chervonenkis dimension | Probably approximately correct learning