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From: Matt Williams <matthew.williams@cancer.org.uk>
Date: Mon, 11 Jun 2007 15:15:33 +0100
Message-ID: <466D5905.2010901@cancer.org.uk>
To: "Kashyap, Vipul" <VKASHYAP1@PARTNERS.ORG>, public-semweb-lifesci@w3.org

I changed the subject line to make it more specific.

I think that Evidence is a tricky, slippery subject. It seems to be both 
traces (i.e. records of something) and in many cases, inferences. Those 
inferences probably shouldn't be called evidence, but they are the 
reason that some data are considered evidence, and others not, and hence 
often get included.

To take the radiology example below

>> So evidence is a function of the facts, the
>> analysis method, the method of inference, and perhaps even the
>> observer (e.g., if the evidence is a radiology image or physical
>> exam, there is inter-observer variation).
>> And it's definitely necessary to relate the hypotheses to the
>> evidence with probabilities
I would suggest that the interpretation of the evidence is a function of 
the facts (plus other things). However, the facts are not stable (e.g. 
with a physical examination) and may conflict with each other; therefore 
inconsistency is not a just a matter of which inference procedure you 
choose, it is also a matter of which facts (your premises) you start from.

It is also not "definitely necessary to relate hypotheses to evidence 
with probability" (although it may be useful). There are a load of other 
techniques that don't use probability: e.g. Wigmore Charts (from 1930's 
onwards) and more recently, non-monotonic logical techniques.

For a good intro. I would recommend David's Schum's book "The Evidential 
Foundations of Probabilistic Reasoning". Also,a look at the evidence 
science website might be good: http://www.evidencescience.org/


Received on Monday, 11 June 2007 14:17:06 UTC

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