Inlier-Based Outlier Detection via Direct Density Ratio Estimation

@article{Hido2008InlierBasedOD,
  title={Inlier-Based Outlier Detection via Direct Density Ratio Estimation},
  author={Shohei Hido and Yuta Tsuboi and Hisashi Kashima and Masashi Sugiyama and Takafumi Kanamori},
  journal={2008 Eighth IEEE International Conference on Data Mining},
  year={2008},
  pages={223-232}
}
We propose a new statistical approach to the problem of inlier-based outlier detection, i.e.,finding outliers in the test set based on the training set consisting only of inliers. Our key idea is to use the ratio of training and test data densities as an outlier score; we estimate the ratio directly in a semi-parametric fashion without going through density estimation. Thus our approach is expected to have better performance in high-dimensional problems. Furthermore, the applied algorithm for… CONTINUE READING
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