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Feature selection is an important problem for pattern classification systems. There are many methods for feature selection available, in which the feature selection method based on mutual information proposed by authors of Ref.[13] is one of the more effective approaches. However, it is often difficult to compute the mutual information for the continuous data whether using discretization strategy...
This work has two main objectives, namely, to introduce a novel algorithm, called the fast condensed nearest neighbor (FCNN) rule, for computing a training-set-consistent subset for the nearest neighbor decision rule and to show that condensation algorithms for the nearest neighbor rule can be applied to huge collections of data. The FCNN rule has some interesting properties: it is order independent,...
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