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Addressing the problem of outlier detection from the viewpoint of statistical learning theory. This method is proposed by Yamanishi, K., Takeuchi, J., Williams, G. et al. (2004) <DOI:10.1023/B:DAMI.0000023676.72185.7c>. It learns the probabilistic model (using a finite mixture model) through an on-line unsupervised process. After each datum is input, a score will be given with a high one indicating a high possibility of being a statistical outlier.
Package details |
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Author | Lizhen Nie <nie_lizhen@yahoo.com> |
Maintainer | Lizhen Nie <nie_lizhen@yahoo.com> |
License | GPL (>= 2) |
Version | 0.1.0 |
Package repository | View on CRAN |
Installation |
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