Title :
Classification with a limited space of features: Improving quality by rejecting misclassifications
Author :
Homenda, Wladyslaw ; Jastrzebska, Agnieszka ; Pedrycz, Witold ; Piliszek, Radoslaw
Author_Institution :
Fac. of Econ. & Inf. in Vilnius, Univ. of Bialystok, Vilnius, Lithuania
Abstract :
Classification, especially in the case of a small space of features, is prone to errors. This is more important when it is costly to gain data from samples to calculate the values for futures. We study what effect limiting the space of features has on the performance of built classifiers and how the quality of classification can be improved by rejecting misclassified elements.
Keywords :
pattern classification; misclassified element rejection; pattern classification; space of features; Accuracy; Computer architecture; Support vector machines; Symmetric matrices; Training; Vectors; Vegetation; pattern recognition; recognition with rejection; reduced space of features; support vector machines;
Conference_Titel :
Information and Communication Technologies (WICT), 2014 Fourth World Congress on
Print_ISBN :
978-1-4799-8114-4
DOI :
10.1109/WICT.2014.7077322
