Title :
A New Heterogeneous Dissimilarity Measure for Data Classification
Author :
Pereira, Cesar Lima ; Cavalcanti, George D C ; Ren, Tsang Ing
Author_Institution :
Center of Inf., Fed. Univ. of Pernambuco, Recife, Brazil
Abstract :
Instance-based learning algorithms typically suffer influences of dissimilarity functions. The problem is frequently related to the Nearest Neighbor rules of these algorithms. This paper will introduce a new dissimilarity measure, called Heterogeneous Centered Difference Measure, which is tested over many known databases. The results are compared with other distance functions.
Keywords :
learning (artificial intelligence); pattern classification; data classification; heterogeneous centered difference measurement; heterogeneous dissimilarity measurement; instance-based learning algorithms; nearest neighbor rules; Accuracy; Databases; Equations; Mathematical model; Measurement; Nearest neighbor searches; Training; distance measure; nearest neighbor;
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2010 22nd IEEE International Conference on
Conference_Location :
Arras
Print_ISBN :
978-1-4244-8817-9
DOI :
10.1109/ICTAI.2010.132
