XPost: comp.ai.neural-nets, sci.image.processing, sci.math.num-analysis   
   From: heath@alumni.brown.edu   
      
   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.   
   >   
   > Many thanks in advance,   
   > Peter.   
      
   The best algorithm depends on the data. MLPs (Multilayer Perceptrons)   
   and RBFs (Radial Basis Functions) are uniform approximators that   
   can provide estimates of conditional class  posterior probabilities.   
      
   However, sometimes the more elementary classifiers (e.g., linear,   
   logistic,   
   quadratic, or k-Nearest Neighbor) yield the best results.   
      
   Before jumping in and trying to obtain quick classification results I   
   often   
   recommend that exploratory data analysis like scatter plots, clustering   
   and PCA be investigated in order to get a better feel for the data.   
      
   Hope this helps.   
      
   Greg   
      
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