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This work considers the results of laboratory investigations carried out to create a system for predicting cardiac necrosis risks that would be based on algorithms and procedures of data mining. Continuous data that indicated changes in the heartbeat and descriptive characteristics of the test animals were used. The procedures of data mining used included the selection of attributes, preprocessing,...
We describe experiments with machine learning algorithms (ID3, C4.5, Bagged-C4.5, Boosted-C4.5 and Naive Bayes) and an algorithm made on the basis of a combination of genetic algorithms (GA) and ID3. To perform the experiments, the latter algorithm is implemented as an extension of the MLC++ library of Stanford University. The behaviour of the algorithm is tested using 24 databases including the databases...
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