Detecting features from confusion matrices using generalized formal concept analysis

Authors:
Carmen Peláez-Moreno;Francisco J. Valverde-Albacete
Affiliations:
Dpto de Teoría de la Señal y de las Comunicaciones, Universidad Carlos III de Madrid, Leganés, Spain;Dpto de Teoría de la Señal y de las Comunicaciones, Universidad Carlos III de Madrid, Leganés, Spain
Venue:
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
Year:
2010

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Abstract

We claim that the confusion matrices of multiclass problems can be analyzed by means of a generalization of Formal Concept Analysis to obtain symbolic information about the feature sets of the underlying classification task We prove our claims by analyzing the confusion matrices of human speech perception experiments and comparing our results to those elicited by experts.