Studies of Stability and Robustness for Artificial Neural Networks and Boosted Decision Trees

@inproceedings{Yang2006StudiesOS,
  title={Studies of Stability and Robustness for Artificial Neural Networks and Boosted Decision Trees},
  author={Huan Yang and Byron P. Roe and Ji Zhu},
  year={2006}
}
In this paper, we compare the performance, stability and robustness of Artificial Neural Networks (ANN) and Boosted Decision Trees (BDT) using MiniBooNE Monte Carlo samples. These methods attempt to classify events given a number of identification variables. The BDT algorithm has been discussed by us in previous publications. Testing is done in this paper by smearing and shifting the input variables of testing samples. Based on these studies, BDT has better particle identification performance… CONTINUE READING
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