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Título:
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A hierarchical perspective to fuzzy inductive reasoning: an attempt to obtain more understandable fuzzy inductive reasoning rules
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Autor/a:
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Bagherpour, Solmaz; Múgica Álvarez, Francisco; Nebot Castells, M. Àngela
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Otros autores:
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Universitat Politècnica de Catalunya. Departament de Ciències de la Computació; Universitat Politècnica de Catalunya. SOCO - Soft Computing |
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Abstract:
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Generalizing hypotheses based on the past data in order to predict the future is the essential core of human learning. Various successful methods and techniques have been developed so far that perform some sort of classification of current data in order to predict future unseen cases. Multi class classification problems are among them as well. In many domains in spite of these automatic techniques, involvement of human experts is crucial. In this paper we are proposing a Hierarchical perspective to Fuzzy Inductive Reasoning (FIR) method as a classifier, in order to provide more insights for experts to the predictive model offered by FIR. Also, This method puts a hierarchical constrain on FIR's generalization which might be useful in finding and predicting exceptional cases of data that don't follow the general rule offered by the model. |
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Abstract:
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Peer Reviewed |
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Materia(s):
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-Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
-Decision support systems
-Soft computing
-classification
-decision making
-fuzzy inductive reasoning
-hierarchical fuzzy inductive reasoning
-Sistemes d'ajuda a la decisió
-Informàtica tova |
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Derechos:
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Tipo de documento:
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Artículo - Versión publicada
Objeto de conferencia |
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