The classifier will probably make mistakes from time to time. I would
try to use a threshold which
indicates that a choice is reasonable confident.
If all categories fall below that threshold you can label that item as
unkown.
Jörn
On 10/28/2014 07:19 PM, [email protected] wrote:
Yeah, it looks like they get the same 1/n score...seems kind of hacky to depend
on that, but so far does appear to work. I think I need a confidence score
system that is [0...1] per category rather than normalized such that the sum of
all weights is 1.0.
Is there any option to do this? If not, where does one dig to make such changes?
Patrick Baggett
Online Engineer - Search Team
e: [email protected]
p: +1 (214) 202-8964
-----Original Message-----
From: Mark G [mailto:[email protected]]
Sent: Tuesday, October 28, 2014 9:55 AM
To: [email protected]
Subject: Re: Getting started with OpenNLP
I think if nothing matches the model at all each cat will have the same score
associated.
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