Title :
A Fuzzy Support Vector Machine with Qualitative Regression Preset
Author :
Yicheng Wei ; Watada, Junzo ; Pedrycz, Witold
Author_Institution :
Grad. Sch. of Inf., Waseda Univ., Kitakyushu, Japan
Abstract :
In this paper, we formulate a qualitative classification model by means of qualitative fuzzy regression preset based fuzzy support vector machine (FQR-FSVM). This new model will make it possible to achieve discrimination of output while characterizing membership for each class in terms of multi-dimensional qualitative inputs (attributes). Moreover, the new model will largely shorten the computing time especially for large database by using linear preset of fuzzy qualitative regression classifier to limit the non-linear classification region.
Keywords :
fuzzy set theory; pattern classification; regression analysis; support vector machines; FQR-FSVM; fuzzy support vector machine; large database; multidimensional qualitative inputs; nonlinear classification region; qualitative classification model; qualitative regression preset; Accuracy; Computational modeling; Databases; Fuzzy sets; Mathematical model; Support vector machines; Training; Fuzzy Qualitative Regression classifier; Fuzzy Support Vector Machine (FSVM); Qualitative classification;
Conference_Titel :
Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on
Conference_Location :
Kitakushu
Print_ISBN :
978-1-4673-2138-9
DOI :
10.1109/ICGEC.2012.15