From: csetzkorn@gmail.com   
      
   On Thursday, 15 December 2016 17:57:45 UTC, Dmitry A. Kazakov  wrote:   
   > On 2016-12-15 18:41, Christian Setzkorn wrote:   
   >   
   > > How do you deal with categorical features (e.g. color, gender) in   
   > > TSK  fuzzy rule systems used for regressions. Are they encoded as dummy   
   > > variables, similar to linear regression. Standard fuzzy sets could then   
   > > be defined on a dummy variable's domain [0 ... 1].   
   >   
   > 1. Nominal discrete feature with the enumeration domain: {Red, Blue,   
   > Black, White}.   
   >   
   > 2. Fuzzified continuous domain, e.g. 3-D color space with fuzzy subsets   
   > defined on it, e.g. Red : Color_Space -> [0,1]. What FCL calls "term".   
   >   
   > A fuzzy set over the domain X : {Red, Blue, Black, White} -> [0,1]   
   >   
   > --   
   > Regards,   
   > Dmitry A. Kazakov   
   > http://www.dmitry-kazakov.de   
      
   Hi Dmitry,   
      
   Just to ensure that I fully understand. So for a nominal variable with 4   
   levels: X : {Red, Blue, Black, White} an example fuzzy set would be X : {0.1,   
   0.3, 0.1234, 0.95643}   
      
   Is this correct?   
      
   Thanks.   
      
   Christian   
      
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