Identifying Multi-instance Outliers

@inproceedings{Wu2010IdentifyingMO,
  title={Identifying Multi-instance Outliers},
  author={Ou Wu and Jun Gao and Weiming Hu and Bing Li and Mingliang Zhu},
  booktitle={SDM},
  year={2010}
}
This paper studies a new data mining problem called multiinstance outlier identification. This problem arises in tasks where each sample consists of many alternative feature vectors (instances) that describe it. This paper defines the multi-instance outliers and analyzes the basic types of multiinstance outliers. Two general identification approaches are proposed based on the state-of-the-art (single-instance) outlier detector LOF (local outlier factor). One approach utilizes the underlying… CONTINUE READING

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