is not required to find the minimum or maximum with respect to ω for a fixed m.
The quality of the Bayesian classifier stands or falls with the accuracy of these quantities. Therefore, the next two chapters will treat the question of how those quantities are estimated in practice. The next chapter will focus on the so-called parametrized methods, and the following one will deal with parameter-free methods that work without a model assumption. Besides the technical challenge of how those distributions are mathematically obtained, another issue becomes evident, ...
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