Comparison of spatial classification rules with different conditional distributions of class label
Articles
Giedrius Stabingis
Klaipėda University, Lithuania
Kęstutis Dučinskas
Klaipėda University, Lithuania
Lijana Stabingienė
Klaipėda University, Lithuania
Published 2014-01-20
https://doi.org/10.15388/NA.2014.1.7
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Keywords

Bayes discriminant functions
supervised classification
spatial dependency

How to Cite

Stabingis G., Dučinskas K. and Stabingienė L. (2014) “Comparison of spatial classification rules with different conditional distributions of class label”, Nonlinear Analysis: Modelling and Control, 19(1), pp. 109-117. doi: 10.15388/NA.2014.1.7.

Abstract

In this paper spatial classification rules based on Bayes discriminant functions are considered. The novelty of this work is that the statistical supervised classification method is improved by extending the influence of spatial correlation between observation to be classified and training sample. Such methods are used for data containing spatially correlated noise. Method accuracy is tested experimentally on artificially corrupted images. This classification rule with distance based conditional distribution for class label shows advantage against other classification rule ignoring such influence and against other commonly used supervised classification methods.

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