Using Fuzzy Clustering to Improve Naive Bayes Classi ers and Probabilisti Networks
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چکیده
منابع مشابه
Improving Naive Bayes Classiiers Using Neuro-fuzzy Learning 1
Naive Bayes classi ers are a well-known and powerful type of classi ers that can easily be induced from a dataset of sample cases. However, the strong conditional independence and distribution assumptions underlying them can sometimes lead to poor classi cation performance. Another prominent type of classi ers are neuro-fuzzy classi cation systems, which derive (fuzzy) classi ers from data usin...
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Although probabilistic networks and fuzzy clustering may seem to be disparate areas of research, they can both be seen as generalizations of naive Bayes classifiers. If all descriptive attributes are numeric, naive Bayes classifiers often assume an axis-parallel multidimensional normal distribution for each class. Probabilistic networks remove the requirement that the distributions must be axis...
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