Description Usage Arguments Details Value Note Author(s) See Also Examples
Produces a specified number of optpart
solutions from random starts, keeping the best result of the set
1 |
dist |
an object of class ‘dist’ from |
numclu |
the number of clusters desired |
numrep |
the number of random starts requested |
maxitr |
the maximum number of iterations per replicate |
calls function optpart
with an random initial
assignment of items to clusters ‘numitr’ times, keeping the best result
(highest within/among ratio observed). See optpart
for more details.
an object of class partana, with components:
ptc |
the mean similarity of each item to each cluster |
ctc |
the mean similarity of each cluster to other clusters |
musubx |
the membership of each item in each cluster |
clustering |
the best ‘crisp’ partition from musubx |
ratio |
the within-cluster/among-cluster similarity ratio achieved at each iteration of the selected result. |
This is a simple wrapper function to automate independent random starts of function optpart.
David W. Roberts droberts@montana.edu
1 2 3 4 5 |
Loading required package: cluster
Loading required package: labdsv
Loading required package: mgcv
Loading required package: nlme
This is mgcv 1.8-25. For overview type 'help("mgcv-package")'.
Loading required package: MASS
Attaching package: 'labdsv'
The following object is masked from 'package:stats':
density
Loading required package: plotrix
Attaching package: 'optpart'
The following object is masked from 'package:labdsv':
clustify
Ratios for respective optparts
[1] "4.123" "4.123" "2.993" "2.988" "2.988" "2.988" "2.993" "2.796" "2.993"
[10] "4.123"
Choosing # 2 ratio = 4.123
Number of clusters = 5
1 2 3 4 5
7 1 3 28 111
[,1] [,2] [,3] [,4] [,5]
[1,] 0.12578378 0.035825098 0.02065326 0.035951111 0.04131058
[2,] 0.03582510 0.000000000 0.00000000 0.004538691 0.01827140
[3,] 0.02065326 0.000000000 0.35148290 0.098675901 0.01567215
[4,] 0.03595111 0.004538691 0.09867590 0.249659368 0.07002854
[5,] 0.04131058 0.018271397 0.01567215 0.070028536 0.24108138
Ratio of Within-cluster similarity/Among-cluster similarity = 4.123 in 59 iterations
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