From: initaalbert@yahoo.com   
      
   hi, i'm an informatics student that doing reseach about boosting   
   algorithm for my final project, i read many paper about variant of   
   boosting algorithm especially AdaBoost, but i'm getting confused about   
   example that can be reweighting or resampling in the next round that   
   depends on error that the example got.   
   my questions is:   
   1. what is the meaning of reweighting? and is there any method for   
   reweighting?   
   2. what kind of algorithm that can used weight for its training,   
   because in WEKA, when i'm using AdaBoost.M1 and decision stumps for   
   its weak learner, Decision Stumps can received weight for its   
   training, i think decision stumps only use entropy calculation for its   
   output (hypothesis), so how come decision stumps use weight in the   
   training process? or i'm wrong?   
   could anyone help me? thx... (btw, sorry if my english isn't good)   
      
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