XPost: comp.ai.neural-nets, sci.image.processing, sci.math.num-analysis   
      
   Phil Sherrod wrote:   
   > On  2-Dec-2005, MajorSetback@excite.com wrote:   
   >   
   > > I would like to separate two classes based upon 8 metrics.  I am   
   > > thinking of using supervised classification based upon defining a   
   > > decision hypersurface in 8-dimensional space.  I would be most grateful   
   > > if someone could suggest the best algorithm for this purpose.   
   >   
   > A Support Vector Machine performs hyperplane separation.  A decision tree   
   also   
   > would be a good method.   
      
   Many thanks for reply.  What I have now is probably like a decision   
   tree since I have a set of (known) reliability metrics and am seeting   
   threshold for them based upon a training set.  However I think a   
   decision tree forms hypercubes (if the metrics are orthogonal).  I   
   would prefer a hypersurface, or perhaps a hyperplane.  However, I will   
   look into Support Vector Machines.   
      
   Thanks again,   
   Peter.   
      
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