Description Usage Arguments Details Value Author(s) References See Also Examples
ROBIN
searches for k initial cluster seeds for k-means-based clustering methods.
1 |
D |
A distance matrix calculated on |
data |
A data matrix with n observations and p variables. |
k |
The number of cluster centers to find. |
mp |
The number of the nearest neighbors to find dense regions by LOF, the default is 10. |
critRobin |
The cutoff value for LOF to determine the observations in the dense regions, the default is 1.05. |
The centers are the observations located in the most dense region and far away from each other at the same time.
In order to find the observations in the highly dense region, ROBIN uses LOF
(Local Outlier Factor, Breunig et al (2000)), see more details lof
.
centers |
A numeric vector of |
lof |
A real vector of local outlier factor values. |
Sarka Brodinova <sarka.brodinova@tuwien.ac.at>
Hasan AM, et al. Robust partitional clustering by outlier and density insensitive seeding. Pattern Recognition Letters, 30(11), 994-1002, 2009.
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