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1 Image Processing & Communications

1 2003

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Distance based classifiers and their use to analysis of data concerned acute coronary syndromes

Jóźwik A., Stawska Z., Grabowski M., Filipiak K., Rudowski R., Opolski G.

Image Processing & Communications

2003

Vol. 9, no 3-4

45-52

The paper presents effectiveness of classifiers based on distance function in application to real problem concerned acute coronary syndromes. The types of decision rules: the standard k-NN rule; its fuzzy version and the multistage decision rule that uses the class overlap idea are considered. In the case of the fuzzy k-NN rule the fuzzyness is applied only for decreasing a misclassification rate. The multistage classifier is taken into account because of its very desired property, which consist in possibility of determination whether a case being classified is difficult or easy for recognition. The more difficult is the case to be classified the more stages are required. This property enables an error rate gradation. In each stage the proposed classifier can make up one of the three following decisions: indicate a class number, reply :"I do not know" or qualifythe object to the next stage. A number of stages depend on the classified object. The analyzed data concern to the two-class decision problem that consist in prediction whether the patient will survive the period of one month or not.