Abstract (EN):
The application of a classification method to a dataset produces, on the objects to classify, a group of
classes organized second a structure (a partition, a hierarchy, a covering, a pyramid, etc.). This structure
depends, not only of the dataset, but also of the intrinsic nature of the classification method used. When a
classificatory structure is obtained becomes important to discover which part is exclusive responsibility of
the used method. This aspect is one of the problems studied in Cluster Validation. A tool of great usefulness
in validation is the random generation of classification structures.
The motivation to develop generation algorithms of classification structures have been intensifying
among the scientific community, leading to several studies. In this work a random generation method of
pyramidal structures is presented and discussed. This method appears as an extension of previous works in
random generation of dendrograms developed by Lapointe and Legendre (1991), Sousa (2000) and Podani
(2000). The dendrograms considered in these works are fully ranked dendrograms, i. e., they are generated
under the three aspects that characterize them completely: the topology, the aggregation level indexes and the
terminal nodes. In the characterization of a pyramid the three referred aspects must also be considered and
the pyramids random generation presented in this work takes account all of them. Fixed a number of terminal
nodes of the pyramid the developed algorithm generates a random pyramid, generating in each level the two
classes to be merge, among the possible classes. A simulation study is made to evaluate the performance of
the algorithm. In particular is analyzed if the method generates pyramids in a uniform way, in sense of
Furnas (1984).
Language:
Portuguese
Type (Professor's evaluation):
Scientific
Contact:
Fernanda Sousa