Two measures:
The first  measure   1 - | a - b |  where a = 1000, and b = 100    .:   -900. 
I said that I wasn't quite happy with this measure but the value is still less 
than 1. So I was willing to work with it. 
The second measure   1 / ( 1 + | a - b |)  where a = 1000, and b = 100   .:  
0.0011098
The second measure is better because the value falls within the range -1 to +1. 
 
So I'm happier with Aaron Hosford's recommendation.

Michael.

Date: Sat, 22 Feb 2014 10:59:23 +0800
Subject: Re: [agi] Numeric Similarity
From: [email protected]
To: [email protected]


I don't understand...
if a=1000 and b = 100, then
a-b=900
so
1 - | a - b | = 1-900 = -899

That doesn't make sense as a similarity score...
Your posited measure seems only applicable when |a-b|<=1, which indeed would be 
the case if a and b lie in [-1.1]

-- Ben


On Sat, Feb 22, 2014 at 10:56 AM, Piaget Modeler <[email protected]> 
wrote:




A and B are any two numbers that can be represented computationally. 
We are looking for the similarity of any two numbers as part of a larger 
similarity based matching scheme. The function Aaron provided will allow 
the similarity to be computed in the range 0 .. +1 which is fine.  As longas 
it's between -1 and +1 it will do. 
Cheers,
Michael.

Date: Sat, 22 Feb 2014 09:54:20 +0800
Subject: Re: [agi] Numeric Similarity
From: [email protected]
To: [email protected]



I assume your numbers a and b are between -1 and 1?  you didn't mention that in 
your original email ! ...

On Fri, Feb 21, 2014 at 10:02 PM, Piaget Modeler <[email protected]> 
wrote:





Thanks to all respondents. 
In the end I found a classic numeric similarity metric:    1 - | a - b |
It's not ideal since numeric scores can dominate other attribute scores.

Ergo, I have to devise a good weighting scheme.
Nothing's perfect I suppose.


Cheers,
~ PM


                                          


  
    
      
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"In an insane world, the sane man must appear to be insane". -- Capt. James T. 
Kirk




  
    
      
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