RaPKod-package: Random Projection Kernel Outlier Detector
In RaPKod: Random Projection Kernel Outlier Detector
Description
Details
Author(s)
References
See Also
Description
The RaPKod package implements a kernel method made for outlier detection. Namely, given a data set of reference typical observation (non-outliers or inliers), it tests each new observation in an online way to determine whether it is an outlier or not. This method uses random low-dimensional projections in a kernel space to build a test statistic whose asymptotic null-distribution (ie when the tested observation is not an outlier) is known. The RaPKod method has two parameters: gamma - the hyperparameter of the (Gaussian) kernel used - and p - the dimensionality of the random projection in the kernel space.
Details
The package consists of two functions: the main function "rapkod" and the auxilary function "od.opt.param" which computes optimal parameters values in RaPKod.
Author(s)
Jeremie Kellner
Maintainer: Jeremie Kellner <jeremie.kellner@ed.univ-lille1.fr>
References
Kellner J., "Gaussian Models and Kernel Methods", PhD thesis, Universite des Sciences et Technologies de Lille (defended on December 1st, 2016)
See Also
RaPKod documentation built on May 2, 2019, 5:58 a.m.
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Description Details Author(s) References See Also
Description
The RaPKod package implements a kernel method made for outlier detection. Namely, given a data set of reference typical observation (non-outliers or inliers), it tests each new observation in an online way to determine whether it is an outlier or not. This method uses random low-dimensional projections in a kernel space to build a test statistic whose asymptotic null-distribution (ie when the tested observation is not an outlier) is known. The RaPKod method has two parameters: gamma - the hyperparameter of the (Gaussian) kernel used - and p - the dimensionality of the random projection in the kernel space.
Details
The package consists of two functions: the main function "rapkod" and the auxilary function "od.opt.param" which computes optimal parameters values in RaPKod.
Author(s)
Jeremie Kellner
Maintainer: Jeremie Kellner <jeremie.kellner@ed.univ-lille1.fr>
References
Kellner J., "Gaussian Models and Kernel Methods", PhD thesis, Universite des Sciences et Technologies de Lille (defended on December 1st, 2016)
See Also
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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