In this paper a hybrid system and a hierarchical neural-net approaches are proposed to solve the automatic labeling problem for unsupervised clustering. The first method consists in the application of nonneural clustering algorithms directly to the output of a neural net; the second one is based on a multilayer organization of neural units. Both methods are a substantial improvement with respect to the most important unsupervised neural algorithms existing in literature. Experimental results are shown to illustrate clustering performance of the systems. © 1999 IEEE.

Automated labeling for unsupervised neural networks: a hierarchical approach

Capuano N.;
1999-01-01

Abstract

In this paper a hybrid system and a hierarchical neural-net approaches are proposed to solve the automatic labeling problem for unsupervised clustering. The first method consists in the application of nonneural clustering algorithms directly to the output of a neural net; the second one is based on a multilayer organization of neural units. Both methods are a substantial improvement with respect to the most important unsupervised neural algorithms existing in literature. Experimental results are shown to illustrate clustering performance of the systems. © 1999 IEEE.
1999
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/141821
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