Neural networks, genetic algorithms and the K-means algorithm: in search of data classification

Neural networks, genetic algorithms, and the K-means clustering algorithm have been used in this study for the classification of quantitative electromyographic data. The results that have been independently obtained by the above methods are presented and the relative advantages and disadvantages are discussed. The comparative study of these methods guidance in choosing the most appropriate method for the classification of electromyographic data. It is also suggested that the problem of medical diagnosis can be handled better by combining more than one method.<
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