On Mon, Feb 25, 2008 at 8:18 PM, Ed Porter <[EMAIL PROTECTED]> wrote:
>
>  As you all know the Naïve Bayes formula for the conditional probability of H
>  given evidence E1, E2,...EN is
>
>  p(H|E1,E2,...EN) = p(H)  *  p(E1|H)/p(E1)  *  p(E2|H)/p(E2)  *...*
>  p(EN|H)/p(EN)

Hi Ed,

This variant is more restricted than is necessary in some cases: it
needs not just conditional independence of Ei on hypothesis, that is
P(Ei|Ej,H)=P(Ei|H), but also mutual independence of Ei, that is
P(E1,...,En)=P(E1)*...*P(En).

Using P(Ei,H)=P(Ei|H)*P(H)=P(H|Ei)*P(Ei), or
P(Ei|H)/P(Ei)=P(H|Ei)/P(H) you expressed the formula in terms of
P(H|Ei) and P(H) rather than P(Ei), P(Ei|H) and P(H). It's clearly
equivalent, but it also introduces (n-1)'th power of P(H), which will
have to figure in MAP and looks more cumbersome.

-- 
Vladimir Nesov
[EMAIL PROTECTED]

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agi
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