1.AdaBoost updates the weight of the sample By the current weak classifier in training each stage. Why doesn't it use the all of the previous weak classifiers to update the weight. (I had tested it that it converged slowly if I used the previous weak classifiers to update the weight )
2.It need to normalize the weight to 1 after updating(just need to multiply factor). I think this step can be omitted in implementing. Right?