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Títol:
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ICA as a preprocessing technique for classification
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Autor/a:
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Sánchez Poblador, Víctor Manuel; Monte-Moreno, Enric; Solé-Casals, Jordi
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Altres autors:
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Universitat de Vic. Escola Politècnica Superior; Universitat de Vic. Grup de Recerca en Tecnologies Digitals; International Conference ICA (5è : 2004: Granada); ICA 2004 |
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Notes:
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In this paper we propose the use of the independent component
analysis (ICA) [1] technique for improving the classification rate of decision
trees and multilayer perceptrons [2], [3]. The use of an ICA for the preprocessing
stage, makes the structure of both classifiers simpler, and therefore
improves the generalization properties. The hypothesis behind the proposed
preprocessing is that an ICA analysis will transform the feature space into a
space where the components are independent, and aligned to the axes and
therefore will be more adapted to the way that a decision tree is constructed.
Also the inference of the weights of a multilayer perceptron will be much easier
because the gradient search in the weight space will follow independent
trajectories. The result is that classifiers are less complex and on some databases
the error rate is lower. This idea is also applicable to regression |
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Matèries:
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-Tractament del senyal
-Separació (Tecnologia) |
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Drets:
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(c) Springer (The original publication is available at www.springerlink.com)
Tots els drets reservats
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Tipus de document:
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Objecte de conferència |
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Publicat per:
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Springer
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