DocumentCode
930350
Title
On the profit of taking into account the known number of objects per class in classification methods (Corresp.)
Author
Slot, R.E.
Volume
25
Issue
4
fYear
1979
fDate
7/1/1979 12:00:00 AM
Firstpage
484
Lastpage
488
Abstract
In the classification problem for chromosomes there are
chromosomes which must be classified into
populations
having known probability distributions. It is further known that these N chromosomes have
in class
. This is a compound decision problem whose optimal solution gives a classification algorithm which is not currently useful in practice because of its long computation time. Two other classification methods are considered, and the results are compared. One is the method often used for the classification of the 46 human chromosomes, where the knowledge about the exact number of chromosome types is disregarded, and only the {sl a priori} probability that a chromosome originates from population
is used. The other method permits only classifications with the correct number of objects in each class and selects from all the possible classifications that one which has the maximum likelihood function. This last method has some advantages for a small number of objects, particularly if the numbers of objects in the classes are equal.
chromosomes which must be classified into
populations
having known probability distributions. It is further known that these N chromosomes have
in class
. This is a compound decision problem whose optimal solution gives a classification algorithm which is not currently useful in practice because of its long computation time. Two other classification methods are considered, and the results are compared. One is the method often used for the classification of the 46 human chromosomes, where the knowledge about the exact number of chromosome types is disregarded, and only the {sl a priori} probability that a chromosome originates from population
is used. The other method permits only classifications with the correct number of objects in each class and selects from all the possible classifications that one which has the maximum likelihood function. This last method has some advantages for a small number of objects, particularly if the numbers of objects in the classes are equal.Keywords
Biological cells; Biological systems; Pattern classification; Biological cells; Humans; Probability distribution; Publishing; Random variables; Time sharing computer systems;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.1979.1056065
Filename
1056065
Link To Document