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By referring to the definition of unbiasedness explain why the estimator which is a constant,
equal to 4.6, say, is poor, in spite of it
Solution
A naive Bayes classifier is a simple probabilistic classifier based on applying
Bayes' theorem with strong (naive) independence assumptions. A more descriptive term for the
underlying probability model would be "independent feature model". A general overview of
statistical classifiers is given here.

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By referring to the definition of unbiasedness explain why the estim.pdf

  • 1. By referring to the definition of unbiasedness explain why the estimator which is a constant, equal to 4.6, say, is poor, in spite of it Solution A naive Bayes classifier is a simple probabilistic classifier based on applying Bayes' theorem with strong (naive) independence assumptions. A more descriptive term for the underlying probability model would be "independent feature model". A general overview of statistical classifiers is given here.