Thanks
It makes more sense now.
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Sent: Sunday, December 12, 2004 11:12 PM
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Subject: Classifier4j-devel digest, Vol 1 #78 - 2 msgs
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Today's Topics:
1. RE: What does this method do -normaliseSigni
ficance( ) (Nick Lothian)
--__--__--
Message: 1
From: Nick Lothian <nic...@es...>
To: "'cla...@li...'"
<cla...@li...>
Subject: RE: [Classifier4j-devel] What does this method do -normaliseSigni
ficance( )
Date: Mon, 13 Dec 2004 08:51:29 +1030
Reply-To: cla...@li...
>=20
> On Fri, 2004-12-10 at 17:45, Wayne Snyder wrote:
> > I understand just about everything that=A2s going on in this =
package,
> > except for the following method:
> >
> > Class BayesianClassifier
>=20
> > protected static double normaliseSignificance(double sig)
>=20
> > Could you please explain the role it plays.
>=20
> I am not a Classifier4J developer but I've used Classifier4J=20
> quite a bit
> and have done a lot of research on Naive Bayesian Classifiers.
>=20
> Stated simply, probabilities of 0 mess up a Naive Bayesian Classifier
> and probabilities of 1 don't change anything. It basically boils =
down
> to the fact that anything multiplied by 0 is 0 and multiplying by 1
> doesn't change anything.=20
> BayesianClassifer.normaliseSignificance(double) simply removes the =
1's
> and the 0's and replaces them with 0.99 and 0.01, respectively.
>=20
> For a good explanation of the magic that is Naive Bayesian
> Classification, check out:
> http://en.wikipedia.org/wiki/Naive_Bayesian_classifier
>=20
> -Mike
>=20
That's exactly what that method does.
Nick
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