find_best_km: Find a best k for the k-means clustering
In jokergoo/cola: A Framework for Consensus Partitioning
find_best_km R Documentation
Find a best k for the k-means clustering
Description
Find a best k for the k-means clustering
Usage
find_best_km(mat, max_km = 15)
Arguments
mat
A matrix where k-means clustering is executed by rows.
max_km
Maximal k to try.
Details
The best k is determined by looking for the knee/elbow of the WSS curve (within-cluster sum of square).
Note this function is only for a rough and quick estimation of the best k.
Examples
# There is no example
NULL
jokergoo/cola documentation built on Feb. 29, 2024, 1:41 a.m.
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| find_best_km | R Documentation |
Find a best k for the k-means clustering
Description
Find a best k for the k-means clustering
Usage
find_best_km(mat, max_km = 15)
Arguments
mat |
A matrix where k-means clustering is executed by rows. |
max_km |
Maximal k to try. |
Details
The best k is determined by looking for the knee/elbow of the WSS curve (within-cluster sum of square).
Note this function is only for a rough and quick estimation of the best k.
Examples
# There is no example
NULL
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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