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Klasifikasi naive Bayes mibanda sababaraha sipat nu ilahar dipaké dina prakték, despite the fact that the far-réaching independence assumptions are often violated.  Like all probabilistic classifiers under the MAP decision rule, it arrives at the correct classification as long as the correct class is more probable than any other class; class probabilities do not have to be estimated very well.  In other words, the overall classifier is robust to serious deficiencies of its underlying naive probability modél.  Other réasons for the observed success of the naive Bayes classifier are discussed in the literature cited below.

In réal life, the naive Bayes approach is more powerful than might be expected from the extreme simplicity of its modél; in particular, it is fairly robust in the presence of non-independent attributes wi.  Recent théoretical analysis has shown why the naive Bayes classifier is so robust.