An Evaluation of Two Algorithms for Hierarchical Classes Analysis

Iwin Leenen and Iven Van Mechelen

Journal of Classification, 2001, vol. 18, issue 1, 57-80

Abstract: In this procedure, a least-squares loss function in terms of discrepancies between D and M is minimized. The present paper describes the original hierarchical classes algorithm proposed by De Boeck and Rosenberg (1988), which is based on an alternating greedy heuristic, and proposes a new algorithm, based on an alternating branch-and-bound procedure. An extensive simulation study is reported in which both algorithms are evaluated and compared according to goodness-of-fit to the data and goodness-of-recovery of the underlying true structure. Furthermore, three heuristics for selecting models of different ranks for a given D are presented and compared. The simulation results show that the new algorithm yields models with slightly higher goodness-of-fit and goodness-of-recovery values. Copyright Springer-Verlag New York Inc. 2001

Date: 2001
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DOI: 10.1007/s00357-001-0005-2

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