Leistungsanalyse von Klassifikatoren mit einem Data-Mining-Tool

Recently, data mining classification has established itself remarkably in the medical field. Machine learning is an emerging area for understanding and analyzing vast amounts of health data. This research work focuses on the performance analysis of various classification methods for healthcare datasets using the machine learning program Weka. We applied different classifiers to four medical datasets to determine the best classification algorithm. The results show that the J48 algorithm and the Random Forest algorithm yield the most promising results among all classification algorithms.