KeyFeature: Determine key features of each overlap clusters.
In boclust: A Clustering Method Based on Boosting on Single Attributes
Description
Usage
Arguments
Value
Description
Determine key features of each overlap clusters.
Usage
1
KeyFeature(cdata, cri, sum.clu)
Arguments
cdata
Overlap clustering result.
cri
A tuning parameter, if p value smaller than cri, then reject
the NULL hypothesis and merge overlap sub-clusters. And cri can be any numeric less
than 1, if cri = 1 then the criteria will be reset to 0.05/N
(N is the number of all overlap sub-cluster), and if cri = 2 then the
criteria 0.05/N(N-1).
Value
A list including the recommend parameter to cut trees in HC scrit0, scrit1,
the separate overlap sub-clusters sep.clu, and highly similar sub-clusters mer.clu,
statistics for merging clu.math.stat
boclust documentation built on Dec. 4, 2017, 9:04 a.m.
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Description Usage Arguments Value
Description
Determine key features of each overlap clusters.
Usage
1 | KeyFeature(cdata, cri, sum.clu)
|
Arguments
cdata |
Overlap clustering result. |
cri |
A tuning parameter, if p value smaller than cri, then reject
the NULL hypothesis and merge overlap sub-clusters. And cri can be any numeric less
than |
Value
A list including the recommend parameter to cut trees in HC scrit0, scrit1,
the separate overlap sub-clusters sep.clu, and highly similar sub-clusters mer.clu,
statistics for merging clu.math.stat
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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