Combinatorial data analysis (CDA) refers to a wide class of methods
for the study of relevant data sets in which the arrangement of a
collection of objects is absolutely central. The focus of this
monograph is on the identification of arrangements, which are then
further restricted to where the combinatorial search is carried out
by a recursive optimization process based on the general principles
of dynamic programming (DP).
The authors provide a comprehensive and self-contained review
delineating a very general DP paradigm or schema that can serve two
functions. First, the paradigm can be applied in various special
forms to encompass all previously proposed applications suggested
in the classification literature. Second, the paradigm can lead
directly to many more novel uses. An appendix is included as a
user's manual for a collection of programs available as
freeware.
The incorporation of a wide variety of CDA tasks under one
common optimization framework based on DP is one of the book's
strongest points. The authors include verifiably optimal solutions
to nontrivially sized problems over the array of data analysis
tasks discussed.
General
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