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Comparison of spatial classification rules with different conditional distributions of class label
- Source :
- Nonlinear analysis : modelling and control, Vilnius : Institute of Mathematics and Informatic, 2014, vol. 19, no. 1, p. 109-117, Nonlinear Analysis, Vol 19, Iss 1 (2014)
- Publication Year :
- 2014
- Publisher :
- Vilnius University Press, 2014.
-
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.
- Subjects :
- supervised classification
Spatial correlation
Bayes discriminant functions
Computer science
business.industry
Applied Mathematics
lcsh:QA299.6-433
spatial dependency
Pattern recognition
Sample (statistics)
lcsh:Analysis
Conditional probability distribution
Class (biology)
Bayes' theorem
ComputingMethodologies_PATTERNRECOGNITION
Discriminant
Classification rule
Artificial intelligence
Noise (video)
supervised classification
business
Analysis
Subjects
Details
- ISSN :
- 23358963 and 13925113
- Volume :
- 19
- Database :
- OpenAIRE
- Journal :
- Nonlinear Analysis: Modelling and Control
- Accession number :
- edsair.doi.dedup.....1bc4cfa971a72fc3515328553369d18a