Alternative prior assumptions for improving the performance of naïve Bayesian classifiers

Author:

Wong Tzu-Tsung

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Information Systems

Reference19 articles.

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2. Anderson DR, Sweeney DJ, Williams TA, Chen JC (2006) Statistics for business and economics: a practical approach, Chap. 7, Thomson Learning

3. Bier VM, Yi W (1995) A Bayesian method for analyzing dependencies in precursor data. Int J Forecast 11: 25–41

4. Blake C, Merz C (1998) UCI machine learning repository, http://www.ics.uci.edu/~mlearn/MLRepository.html .

5. Cestnik B, Bratko I (1991) On estimating probabilities in tree pruning. Machine Learning–EWSL-91, European Working Session on Learning. Springer-Verlag, Berlin, Germany, pp 138–150

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