Description: Evaluation data in the open test of the classification process to remove stop words, the introduction of the Good-Turing algorithm classification performance than the Laplace principle 305 , 100 Lidstone method to select feature words in the cross-entropy algorithm to increase the Good-Turing Bayesian classification than maximum entropy classification performance of 95 through this data smoothing algorithm, can help to overcome the problem of sparse data caused by the lack of feature words
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DataMining3rd.pdf
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