On Mon, Feb 25, 2008 at 2:51 PM, Ed Porter <[EMAIL PROTECTED]> wrote:
> But that does stop people from modeling systems in a simplified manner by
> acting as if these limitations were met. Naïve Bayesian methods are
> commonly used. I have read multiple papers saying that in many cases it
>
Ben,
Thanks for the info.
If you knew of anything relatively simple that was on-line that would be
preferred. But, if not, I guess I could try to Google for something myself.
(Of if I wait long enough there probably will be a simple Wikipedia
explanation.)
Ed Porter
-Original Message---
Vlad,
(1) You are correct that naïve Bayes assumes "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).:" That is
a major limitation, one often not met in reality.
But that does stop people f
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
Last night in bed I came upon what seems to me like a new and at times
useful way to compute naïve Bayesian conditional probabilities.
But since I have never seen it before, and since as I get older I often
overlook things, I though I would share it with those on this list to see
(A) if my math co
