Efficient Multiclass Boosting Classification with Active Learning.

@inproceedings{Huang2007EfficientMB,
  title={Efficient Multiclass Boosting Classification with Active Learning.},
  author={Jian Huang and Seyda Ertekin and Yang Song and Hongyuan Zha and C. Lee Giles},
  booktitle={SDM},
  year={2007}
}
We propose a novel multiclass classification algorithm Gentle Adaptive Multiclass Boosting Learning (GAMBLE). The algorithm naturally extends the two class Gentle AdaBoost algorithm to multiclass classification by using the multiclass exponential loss and the multiclass response encoding scheme. Unlike other multiclass algorithms which reduce the K-class classification task to K binary classifications, GAMBLE handles the task directly and symmetrically, with only one committee classifier. We… CONTINUE READING
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