In this paper a hybrid system and a hierarchical neuralnet approaches are proposed to solve the automatic labeling problem for unsupervised clustering. The first method consists in the application of non neural 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.

Automated Labeling for Unsupervised Neural Networks: a Hierarchical Approach

TAGLIAFERRI, Roberto;CAPUANO, Nicola;
1999-01-01

Abstract

In this paper a hybrid system and a hierarchical neuralnet approaches are proposed to solve the automatic labeling problem for unsupervised clustering. The first method consists in the application of non neural 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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/3675077
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