Spatial information Fuzzy C-mean(SFCM) Presenter: Aydin Ayanzadeh Email:ayanzadeh17@itu.edu.tr StudentID: 708181005 Course : Fuzzy Logic Gulcihan Ozdemir-Fall 2018

1. Spatial information Fuzzy C-mean(SFCM)
Presenter: Aydin Ayanzadeh
Email:ayanzadeh17@itu.edu.tr
StudentID: 708181005
Course : Fuzzy Logic
1
Gulcihan Ozdemir Fall 2018

2. Outline
● Clustering
● Goals of Clustering
● Clustering Application
● K-means
● C-means
● Fuzzy Clustering Application
● Iris dataset segmentation
● KFCM

3. 3

4. 4

5. CSFCM
5

6. Example
6
0.21 0.16 0.23
0.22 0.71 0.15
0.18 0.07 0.19
0.21 0.16 0.23
0.22 0.71 0.15
0.18 0.07 0.19

7. Example
7
h1 = mean (0.21, 0.16, 0.03; 0.22, 0.71, 0.15 ; 0.18, 0.07, 0.19) = 0.2133;
P=1; q=1;
U_new 1= (0.71* 0.2133) / (0.71* 0.2133+ 0.29* 0.7644) = 0.4059
Mean2= h2 = 0.7644;
P=2; q=2;
U_new 1= (0.71 ^ 2* 0.2133 ^ 2) / (0.71 ^ 2* 0.2133 ^ 2+ 0.29 ^ 2* 0.7644 ^ 2) =
0.3182

8. DataSets
8

9. 9

10. Pre-processing Step
10

11. References
● J. C. Dunn (1973): "A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters",
Journal of Cybernetics 3: 32-57
● J. C. Bezdek (1981): "Pattern Recognition with Fuzzy Objective Function Algoritms", Plenum Press, New York
● Tariq Rashid: “Clustering”
● http://www.cs.bris.ac.uk/home/tr1690/documentation/fuzzy_clustering_initial_report/node11.html
● Hans-Joachim Mucha and Hizir Sofyan: “Nonhierarchical Clustering”
● http://www.quantlet.com/mdstat/scripts/xag/html/xaghtmlframe149.html
11

12. 12