Learning Homophily Couplings from Non-IID Data for Joint Feature Selection and Noise-Resilient Outlier Detection

@inproceedings{Pang2017LearningHC,
  title={Learning Homophily Couplings from Non-IID Data for Joint Feature Selection and Noise-Resilient Outlier Detection},
  author={Guansong Pang and Longbing Cao and Ling Chen and Huan Liu},
  booktitle={IJCAI},
  year={2017}
}
This paper introduces a novel wrapper-based outlier detection framework (WrapperOD) and its instance (HOUR) for identifying outliers in noisy data (i.e., data with noisy features) with strong couplings between outlying behaviors. Existing subspace or feature selection-based methods are significantly challenged by such data, as their search of feature subset… CONTINUE READING