DBIndex: Davis-Bouldin-Index
In Budheimer/RDRToolbox: A package for nonlinear dimension reduction with Isomap and LLE.
Description
Usage
Arguments
Details
Value
Author(s)
Examples
Description
Computes the Davis-Bouldin-Index for cluster validation purposes.
Usage
1
Arguments
data
N x D matrix (N samples, D features)
labels
a vector of class labels
Details
To compute a clusters' compactness, this version uses the Euclidean distance to
determine the mean distances between the samples and the cluster centers.
Furthermore, the distance of two clusters is given by the distance of their centers.
Value
'DBIndex' returns the Davis-Bouldin cluster index, a numeric value.
Author(s)
Christoph Bartenhagen
Examples
1
2
3
## DB-Index of a 50 dimensional dataset with 20 samples separated into two classes
d = generateData(samples=20, genes=50, diffgenes=10, blocksize=5)
DBIndex (data=d[[1]], labels=d[[2]])
Budheimer/RDRToolbox documentation built on May 30, 2019, 1:26 p.m.
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Description Usage Arguments Details Value Author(s) Examples
Description
Computes the Davis-Bouldin-Index for cluster validation purposes.
Usage
1 |
Arguments
data |
N x D matrix (N samples, D features) |
labels |
a vector of class labels |
Details
To compute a clusters' compactness, this version uses the Euclidean distance to determine the mean distances between the samples and the cluster centers. Furthermore, the distance of two clusters is given by the distance of their centers.
Value
'DBIndex' returns the Davis-Bouldin cluster index, a numeric value.
Author(s)
Christoph Bartenhagen
Examples
1 2 3 | ## DB-Index of a 50 dimensional dataset with 20 samples separated into two classes
d = generateData(samples=20, genes=50, diffgenes=10, blocksize=5)
DBIndex (data=d[[1]], labels=d[[2]])
|
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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