Document Detail


On the influence of sample set structure on decision rule quality for the case of a linear discriminant function.
MedLine Citation:
PMID:  21868965     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
The influence of sample set structure on decision rule quality for the case of a linear discriminant function is considered. Specifically, the case of missing data in the sample set and the case when the multivariate random variable is to be registered with the help of a single-channel device are investigated. Some rather unusual phenomena are discussed, such as when some new samples are added to the sample set, and as a result the quality of parameter estimations used in a decision rule become better, but at the same time the quality of the decision rule itself becomes worse. The investigation is performed for the classical model of a twocategory classifier when the categories are described by the multivariate normal densities having common covariance matrices. Some results of statistical simulation experiments are included.
Authors:
V Brailovsky
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  IEEE transactions on pattern analysis and machine intelligence     Volume:  3     ISSN:  0162-8828     ISO Abbreviation:  IEEE Trans Pattern Anal Mach Intell     Publication Date:  1981 Apr 
Date Detail:
Created Date:  2011-08-26     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9885960     Medline TA:  IEEE Trans Pattern Anal Mach Intell     Country:  United States    
Other Details:
Languages:  eng     Pagination:  454-9     Citation Subset:  -    
Affiliation:
Department of Computer Science, University of Maryland, College Park, MD 20742.
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