Outlier Detection with Space Transformation and Spectral Analysis

@inproceedings{Assent2013OutlierDW,
  title={Outlier Detection with Space Transformation and Spectral Analysis},
  author={Ira Assent and Xuan-Hong Dang and Barbora Micenkov{\'a} and Raymond T. Ng},
  booktitle={SDM},
  year={2013}
}
Detecting a small number of outliers from a set of data observations is always challenging. In this paper, we present an approach that exploits space transformation and uses spectral analysis in the newly transformed space for outlier detection. Unlike most existing techniques in the literature which rely on notions of distances or densities, this approach introduces a novel concept based on local quadratic entropy for evaluating the similarity of a data object with its neighbors. This… CONTINUE READING
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