VC-dimension (after Vapnik and Chervonenkis) is a measure of the power of a set of shapes (ranges) to realize subsets of points. VC-dimension is a vital analysis tool in the fields of machine learning and computational geometry.
VC-dimension (after Vapnik and Chervonenkis) is a measure of the power of a set of shapes (ranges) to realize subsets of points. VC-dimension is a vital analysis tool in the fields of machine learning and computational geometry.