ClusterMethods: Clusters outlier detection methods according to the...
In sevvandi/outselect: Algorithm selection for unsupervised outlier detection
Description
Usage
Arguments
Value
See Also
Examples
Description
Clusters outlier detection methods according to the correlation matrix for min-max and median-iqr normalization methods, using the R package cluster.
Usage
1
ClusterMethods(kk, rocpr = 1, vis = FALSE)
Arguments
kk
The number of clusters
rocpr
If rocpr = 1, then area under ROC cure is used, if rocpr = 2 then area under PR curve is used.
vis
If TRUE then the resulting graphs are plotted.
Value
A pam.object described in the R package cluster.
See Also
Examples
1
2
3
4
5
cls <- ClusterMethods(8)
which(cls$clustering==2)
which(cls$clustering==4)
which(cls$clustering==5)
which(cls$clustering==6)
sevvandi/outselect documentation built on June 1, 2019, 3:58 a.m.
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Description Usage Arguments Value See Also Examples
Description
Clusters outlier detection methods according to the correlation matrix for min-max and median-iqr normalization methods, using the R package cluster.
Usage
1 | ClusterMethods(kk, rocpr = 1, vis = FALSE)
|
Arguments
kk |
The number of clusters |
rocpr |
If |
vis |
If |
Value
A pam.object described in the R package cluster.
See Also
Examples
1 2 3 4 5 | cls <- ClusterMethods(8)
which(cls$clustering==2)
which(cls$clustering==4)
which(cls$clustering==5)
which(cls$clustering==6)
|
R Package Documentation
Browse R Packages
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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