Boosting with Averaged Weight Vectors

@inproceedings{Oza2003BoostingWA,
  title={Boosting with Averaged Weight Vectors},
  author={Nikunj C. Oza},
  booktitle={Multiple Classifier Systems},
  year={2003}
}
AdaBoost !5] is a well-known ensemble learning algorithm that constructs its constituent or base models in sequence. A key step ill AdaBoost is constructing a distribution over the training examples to crette each base model. This distribution, represented as a vector, is constructed to be orthogonal to the vector of mistakes made by tLe previous base model in the sequence [6]. The idea is to make file next base model's errors uncorrelated with those of the previol_s model. Some researchers… CONTINUE READING
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