Proc. 11th Int. Workshop on Algorithmic Learning Theory
H. Arimura, S. Jain & A. Sharma (eds), Sydney,
pp56-70, LNCS #1968
by L. J. Fitzgibbon, L. Allison & D. L. Dowe
Given a series of multivariate data, approximate it by a piece-wise
constant function. How many cut-points are there? What are the means
and variances of the segments? Where should the cut points be placed?
The simplest model is a single segment. The most complex model has
one segment per data point. The best model is generally somewhere
between these extremes. Only by considering model complexity can
a reasonable inference be made.