runLouvain.R
- runLouvain(res, ensemble_num)
The Louvain clustering algorithm is employed to address the non-linear embedding in the latent space to produce multiple underlying cluster results to generate cluster ensemble.
- Parameters 1:
- res: default='1'
- Attributes 1:
- res: resolution
- Parameters 2:
- ensemble_num: default='10'
- Attributes 2:
- ensemble_num: number of basic clusterings
Example
run runLouvain.R:
R
source("runLouvain.R")
runLouvain(res=1, ensemble_num = 10)
output:
********************************************** .
output 9 of 1 latent: goolam .
********************************************** .
---------------------------------------------- .
resolution: 1 .
---------------------------------------------- .
Computing nearest neighbor graph
Computing SNN
[1] "============ Louvain ============"
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 124
Number of edges: 4005
Running Louvain algorithm...
0% 10 20 30 40 50 60 70 80 90 100%
----|----|----|----|----|----|----|----|----|----|
**************************************************|
Maximum modularity in 10 random starts: 0.4066
Number of communities: 4
Elapsed time: 0 seconds
...
...
...
********************************************** .
output 9 of 9 latent: goolam .
********************************************** .
---------------------------------------------- .
resolution: 1 .
---------------------------------------------- .
Computing nearest neighbor graph
Computing SNN
[1] "============ Louvain ============"
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 124
Number of edges: 4005
Running Louvain algorithm...
0% 10 20 30 40 50 60 70 80 90 100%
----|----|----|----|----|----|----|----|----|----|
**************************************************|
Maximum modularity in 10 random starts: 0.4066
Number of communities: 4
Elapsed time: 0 seconds
The Louvain_resolution_1.csv is produced and saved in the ./OutputData.