Comparison of Bayesian and Neural Net Unsupervised
نویسندگان
چکیده
Unsupervised classiication is the classiication of data into a number of classes in such a way that data in each class are all similar to each other. In the past there have been few if any studies done to compare the performance of diierent unsupervised classiication techniques. In this paper we review Bayesian and neural net approaches to unsupervised classiication and present results of experiments that we did to compare Autoclass, a Bayesian classiication system, and ART2, a neural net classiication algorithm.
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