Title :
A pattern classifier for interval-valued data based on multinomial logistic regression model
Author :
de Barros, A.P. ; de Assis Tenorio de Carvalho, F. ; de Andrade Lima Neto, E.
Author_Institution :
Inst. Fed. de Educ., Cienc. e Tecnol. da Paraiba, João Pessoa, Brazil
Abstract :
Interval-valued data arise in practical situations such as recording monthly interval temperatures at meteorological stations, daily interval stock prices, etc. This paper introduces a multinomial logistic regression method for interval-valued data in order to classify items described by interval-valued variables into a pre-defined number of a priori classes. Applications of the proposed approach on real as well as synthetic interval-valued data sets showed the usefulness of this approach.
Keywords :
pattern classification; regression analysis; interval-valued variables; item classification; multinomial logistic regression model; pattern classifier; real interval-valued data sets; synthetic interval-valued data sets; Data analysis; Data models; Databases; Error analysis; Logistics; Mathematical model; Vectors; Multinomial logistic regression; interval-valued data; symbolic data analysis;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4673-1713-9
Electronic_ISBN :
978-1-4673-1712-2
DOI :
10.1109/ICSMC.2012.6377781
