XPost: comp.soft-sys.matlab   
   From: not@here.com   
      
   Hi,   
      
   Newbie.   
      
   The examples I've seen in the fuzzy world all relate to categorising one   
   item of data at a time.   
   Are there any straightforward "standard" paradigms out there to classify a   
   data item based on grouped data results?   
      
   For example, say I have this training data set.   
      
   X =1,2,1,3,4,2,4,1 (interval category)   
   Y= 3,6,3,6,8,3,4,1 (response)   
      
   As we can see from this toy data the highest or "best"  response may be seen   
   to be around 4 tailing away from this.   
      
   So, when I have a new data item to classify, say a 3, I can give a   
   prediction for its response. Linguistically, I would wish to classify as a   
   "Preference", Say "most preferred", "neutral", "least preferred" - I know   
   how to defuzz, I'm just stating this to give a flavour of what I'm after.   
      
   I know I can use standard distribution stats such as mean and standard   
   deviation, but I wondered how the fuzzy world would view this problem. In   
   fact would a method be to formulate the fuzzy sets based on such   
   distribution stats.   
      
   Any thoughts, references etc appreciated.   
      
   TIA   
      
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