1 |
Arbelaitz, O., Gurrutxaga, I., Muguerza, J., Perez, J.M., and Perona, I., An extensive comparative study of cluster validity indices, Pattern Recognition, 2013, Vol. 46, No. 1, pp. 243-256.
DOI
|
2 |
He, S., Wu, Q.H., and Saunders, J.R., Group search optimizer : an optimization algorithm inspired by animal searching behavior, IEEE transactions on evolutionary computation, 2009, Vol. 13, No. 5, pp. 973-990.
DOI
|
3 |
Hruschka, E.R. and Ebecken, N.F., A genetic algorithm for cluster analysis, Intelligent Data Analysis, 2003, Vol. 7, No. 1, pp. 15-25.
|
4 |
Hruschka, E.R., Campello, R.J., and Freitas, A.A., A survey of evolutionary algorithms for clustering, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 2009, Vol. 39, No. 2, pp. 133-155.
DOI
|
5 |
Kang, B.S. and Kim S.S., Combined Artificial Bee Colony for Data Clustering, Journal of Society of Korea industrial and Systems Engineering, 2017, Vol. 40, No. 4, pp. 203-210.
DOI
|
6 |
Kim, S.S., Baek, J.Y., and Kang, B.S., Group Search Optimization Data Clustering Using Silhouette, Journal of the Korean Operations Research and Management Science Society, 2017, Vol. 42, No. 3, pp. 25-34.
|
7 |
Krishna, K. and Murty, M.N., Genetic K-means algorithm, IEEE Transactions on Systems, Man, and Cybernetics, Part B(Cybernetics), 1999, Vol. 29, No. 3, pp. 433-439.
DOI
|
8 |
Lleti, R., Ortiz, M.C., Sarabia, L.A., and Sanchez, M.S., Selecting variables for k-means cluster analysis by using a genetic algorithm that optimizes the silhouettes, Analytica Chimica Acta, 2004, Vol. 515, No. 1, pp. 87-100.
DOI
|
9 |
Ng, R.T. and Han, J., Efficient and Effective Clustering Methods for Spatial Data Mining, In Proceedings of VLDB, 1994, pp. 144-155.
|
10 |
Park, H.S. and Jun, C.H., A simple and fast algorithm for K-medoids clustering, Expert systems with applications, 2009, Vol. 36, No. 2, pp. 3336-3341.
DOI
|
11 |
Rousseeuw, P.J., Silhouettes : a graphical aid to the interpretation and validation of cluster analysis, Journal of computational and applied mathematics, 1987, Vol. 20, pp. 53-65.
DOI
|
12 |
Ruspini, E.H., Numerical methods for fuzzy clustering, Information Sciences, 1970, Vol. 2, No. 3, pp. 319-350.
DOI
|
13 |
UCI machine learning repository Wine datasets, https://archive.ics.uci.edu/ml/datasets/Wine.
|
14 |
Struyf, A., Hubert, M., and Rousseeuw, P., Clustering in an object-oriented environment, Journal of Statistical Software, 1997, Vol. 1, No. 4, pp. 1-30.
|
15 |
UCI machine learning repository Glass datasets, https://archive.ics.uci.edu/ml/datasets/Glass+Identification.
|
16 |
UCI machine learning repository Iris datasets, https://archive.ics.uci.edu/ml/datasets/Iris.
|
17 |
Xu, R., Xu, J., and Wunsch, D.C., A comparison study of validity indices on swarm-intelligence-based clustering, IEEE Transactions on Systems, Man, and Cybernetics, Part B(Cybernetics), 2012, Vol. 42, No. 4, pp. 1243-1256.
DOI
|
18 |
UCI machine learning repository Breast Cancer datasets, https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Original%29.
|