From: linuxkaffee_@_gmx.net   
      
   Hi,   
      
   I want to use a machine learning-based classification   
   algorithm to generate a classifier. The training set   
   was gathered by supervised learning and consists of about   
   600 examples, each of which has 30 features and a binary   
   label (example belongs to class or not).   
      
   What classification algorithm would yield most accurate   
   results (in terms of minimal classification error) in   
   my case?   
      
   Support Vector Machines seem to be a good choice but I   
   would like to hear your opinion.   
      
   Regards,   
   Stephan   
      
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