Search results for "Classification rule"

showing 3 items of 3 documents

Improving the k-NCN classification rule through heuristic modifications

1998

Abstract This paper presents an empirical investigation of the recently proposed k-Nearest Centroid Neighbours ( k -NCN) classification rule along with two heuristic modifications of it. These alternatives make use of both proximity and geometrical distribution of the prototypes in the training set in order to estimate the class label of a given sample. The experimental results show that both alternatives give significantly better classification rates than the k -Nearest Neighbours rule, basically due to the properties of the plain k -NCN technique.

ComputingMethodologies_PATTERNRECOGNITIONTraining setArtificial Intelligencebusiness.industryClassification ruleSignal ProcessingCentroidPattern recognitionComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftwareMathematicsPattern Recognition Letters
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On the Construction of Optimum Categories in Biomedical Data Recognition Problems

1979

The recognition of patterns within sets of biomedical data involves the following problems: a) Proper recording of the data to be used b) Extraction of suitable features c) Choice of categories or classes which are relevant to the medical decision task d) Estimation of the underlying distributions in the case of using parametric methods e) Choice of an adequate classification rule Whereas a lot of theories and procedures exists for most of these steps — particularly in the field of computer-aided differential diagnosis of electrocardiograms (ECG) (see [6]) — there has been only rare considerations on the problems of definition of appropriate categories.

Pattern vectorComputer sciencebusiness.industryQuadratic classifierMachine learningcomputer.software_genreField (computer science)Task (project management)Biomedical dataClassification ruleParametric methodsArtificial intelligencebusinesscomputer
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An efficient prototype merging strategy for the condensed 1-NN rule through class-conditional hierarchical clustering

2002

Abstract A generalized prototype-based classification scheme founded on hierarchical clustering is proposed. The basic idea is to obtain a condensed 1-NN classification rule by merging the two same-class nearest clusters, provided that the set of cluster representatives correctly classifies all the original points. Apart from the quality of the obtained sets and its flexibility which comes from the fact that different intercluster measures and criteria can be used, the proposed scheme includes a very efficient four-stage procedure which conveniently exploits geometric cluster properties to decide about each possible merge. Empirical results demonstrate the merits of the proposed algorithm t…

Single-linkage clusteringcomputer.software_genreComplete-linkage clusteringHierarchical clusteringk-nearest neighbors algorithmArtificial IntelligenceNearest-neighbor chain algorithmClassification ruleSignal ProcessingCluster (physics)Computer Vision and Pattern RecognitionData miningMerge (version control)computerSoftwareMathematicsPattern Recognition
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