Description Usage Arguments Details Value Slots Author(s) References Examples
Validation index for validating fuzzy clustering result
1 | validation.index(object)
|
object |
fuzzy clustering object |
This function provide several validation indexs that calculated from fuzzy clustering result. Validation index can be used for choose best optimum parameter.
There are PC, MPC, CE, S, Xie Beni, Kwon, and Tang index. PC (Partition Coefficient), MPC (Modified Partition Coefficient), and CE (Classification Entropy) are calculated from membership matrix. S (Separation Index), Xie Beni, Kwon, and Tang use both distance and membership matrix.
The best cluster result can be decided with minimum value of index, except MPC and PC use maximum value.
validation index object.
XB
Xie Beni Index
PC
Partition Coef.
MPC
Modifief Partition Coef.
Kwon
Kwon Index
Tang
Tang Index
S
Separation Index
CE
Classification Entropy
Achmad Fauzi Bagus F
Wang, W., & Zhang, Y. (2007). On Fuzzy Cluster Validity Indices. Fuzzy Sets and System, 2095-2117.
1 2 3 4 | fuzzy.CM(iris[,1:4],K=3,m=2,max.iteration=100,threshold=1e-5,RandomNumber=1234)->cl
validation.index(cl)->valid
#example for Xie Beni index
XB(valid)
|
Membership initialiazed randomly
iteration: 1
iteration: 2
iteration: 3
iteration: 4
iteration: 5
iteration: 6
iteration: 7
iteration: 8
iteration: 9
iteration: 10
iteration: 11
iteration: 12
iteration: 13
iteration: 14
iteration: 15
iteration: 16
iteration: 17
iteration: 18
iteration: 19
iteration: 20
iteration: 21
iteration: 22
iteration: 23
iteration: 24
iteration: 25
iteration: 26
iteration: 27
iteration: 28
Finish :)
[1] 0.1369082
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.