Kim, T.[Taehwan],
Bezdek, J.C.[James C.],
Hathaway, R.J.[Richard J.],
Optimality tests for fixed points of the fuzzy c-means algorithm,
PR(21), No. 6, 1988, pp. 651-663.
WWW Version.
0309
BibRef
And:
Reply to 'Comments on: optimality test for fixed points',
PR(23), No. 11, 1990, pp. 1309-1310.
WWW Version.
0401 See also Comments on: optimality test for fixed points.
BibRef
Xie, X.L.[Xuanli Lisa], and
Beni, G.[Gerardo],
A Validity Measure for Fuzzy Clustering,
PAMI(13), No. 8, August 1991, pp. 841-847.
IEEE Abstract. IEEE Top Reference.
WWW Version.
BibRef
9108
Wei, W.[Wen],
Mendel, J.M.[Jerry M.],
Optimality tests for the fuzzy c-means algorithm,
PR(27), No. 11, November 1994, pp. 1567-1573.
WWW Version.
0401
BibRef
Dave, R.N.,
Validating Fuzzy Partitions Obtained Through C-Shells Clustering,
PRL(17), No. 6, May 15 1996, pp. 613-623.
9607
BibRef
Rezaee, M.R.,
Lelieveldt, B.P.F.,
Reiber, J.H.C.,
A New Cluster Validity Index for the Fuzzy C-Mean,
PRL(19), No. 3-4, March 1998, pp. 237-246.
9807
BibRef
Rezaee, M.R.[M. Ramze],
Goedhart, B.,
Lelieveldt, B.P.F.,
Reiber, J.H.C.,
Fuzzy feature selection,
PR(32), No. 12, December 1999, pp. 2011-2019.
WWW Version.
BibRef
9912
Foody, G.M.[Giles M.],
The Continuum of Classification Fuzziness in Thematic Mapping,
PhEngRS(65), No. 4, April 1999, pp. 443-452.
BibRef
9904
Foody, G.M.,
Sharpening Fuzzy Classification Output to Refine the
Representation of Sub-Pixel Land-Cover Distribution,
JRS(19), No. 13, September 10 1998, pp. 2593-2599.
9810
BibRef
Zahid, N.,
Abouelala, O.,
Limouri, M.,
Essaid, A.,
Unsupervised fuzzy clustering,
PRL(20), No. 2, February 1999, pp. 123-129.
BibRef
9902
Zahid, N.,
Limouri, M.,
Essaid, A.,
A new cluster-validity for fuzzy clustering,
PR(32), No. 7, July 1999, pp. 1089-1097.
WWW Version.
BibRef
9907
Hammah, R.E.[Reginald E.],
Curran, J.H.[John H.],
Validity Measures for the Fuzzy Cluster Analysis of Orientations,
PAMI(22), No. 12, December 2000, pp. 1467-1472.
IEEE Abstract. IEEE Top Reference.
WWW Version.
0012
BibRef
Looney, C.G.[Carl G.],
Interactive clustering and merging with a new fuzzy expected value,
PR(35), No. 11, November 2002, pp. 2413-2423.
WWW Version.
0208
BibRef
Wu, K.L.[Kuo-Lung],
Yu, J.[Jian],
Yang, M.S.[Miin-Shen],
A novel fuzzy clustering algorithm based on a fuzzy scatter matrix with
optimality tests,
PRL(26), No. 5, April 2005, pp. 639-652.
WWW Version.
0501 See also Alternative c-means clustering algorithms.
See also Mean shift-based clustering.
BibRef
Kim, D.W.[Dae-Won],
Lee, K.H.[Kwang H.],
Lee, D.[Doheon],
Fuzzy cluster validation index based on inter-cluster proximity,
PRL(24), No. 15, November 2003, pp. 2561-2574.
WWW Version.
0308
BibRef
Pakhira, M.K.[Malay K.],
Bandyopadhyay, S.[Sanghamitra],
Maulik, U.[Ujjwal],
Validity index for crisp and fuzzy clusters,
PR(37), No. 3, March 2004, pp. 487-501.
WWW Version.
0401
BibRef
Mitchell, H.B.,
On the Dengfeng-Chuntian similarity measure and its application to
pattern recognition,
PRL(24), No. 16, December 2003, pp. 3101-3104.
WWW Version.
0310Dengfeng and Chuntian operator (
See also New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions. )
may give counter-intuitive results.
We show how a simple modification of the operator may
correct this problem
BibRef
Yang, C.C.[Chih-Chung],
Bose, N.K.,
Generating fuzzy membership function with self-organizing feature map,
PRL(27), No. 5, 1 April 2006, pp. 356-365.
WWW Version.
0604Fuzzy membership function; Pattern recognition;
Self-organizing feature map; Computational intelligence
BibRef
Bhatt, R.B.[Rajen B.],
Gopal, M.,
On the extension of functional dependency degree from crisp to fuzzy
partitions,
PRL(27), No. 5, 1 April 2006, pp. 487-491.
WWW Version. Dependency degree; Fuzzy-rough sets; Rough sets
0604
BibRef
Bouguessa, M.[Mohamed],
Wang, S.R.[Sheng-Rui],
Sun, H.J.[Hao-Jun],
An objective approach to cluster validation,
PRL(27), No. 13, 1 October 2006, pp. 1419-1430.
WWW Version.
0606Fuzzy clustering; Validity index; Overlapping clusters;
Overlap rate; Truthed data set
BibRef
Cimino, M.G.C.A.[Mario G.C.A.],
Lazzerini, B.[Beatrice],
Marcelloni, F.[Francesco],
A novel approach to fuzzy clustering based on a dissimilarity relation
extracted from data using a TS system,
PR(39), No. 11, November 2006, pp. 2077-2091.
WWW Version.
0608Fuzzy clustering; Fuzzy identification; Similarity relation
BibRef
Campello, R.J.G.B.,
A fuzzy extension of the Rand index and other related indexes for
clustering and classification assessment,
PRL(28), No. 7, May 2007, pp. 833-841.
WWW Version.
0703Fuzzy clustering; Fuzzy classification; External validity indexes;
Rand index; Adjusted Rand index; Jaccard coefficient; Minkowski measure;
Fowlkes-Mallows index; [Gamma] Statistics
BibRef
Chiang, J.H.[Jung-Hsien],
Yin, Z.X.[Zong-Xian],
Unsupervised minor prototype detection using an adaptive population
partitioning algorithm,
PR(40), No. 11, November 2007, pp. 3132-3145.
WWW Version.
0707Minor prototype; Cluster analysis; Fuzzy clustering; Outlier
BibRef
Ghosh, A.[Ashish],
Meher, S.K.[Saroj K.],
Shankar, B.U.[B. Uma],
A novel fuzzy classifier based on product aggregation operator,
PR(41), No. 3, March 2008, pp. 961-971.
WWW Version.
0711Pattern recognition; Fuzzy classifier; Aggregation operators;
Remote sensing images
BibRef
Garcia-Cascales, M.S.[M. Socorro],
Lamata, M.T.[M. Teresa],
Solving a decision problem with linguistic information,
PRL(28), No. 16, December 2007, pp. 2284-2294.
WWW Version.
0711Decision-making; Maintenance problem; Linguistic information;
Fuzzy sets; Fuzzy distance
BibRef
Celikyilmaz, A.[Asli],
Turksen, I.B.[I. Burhan],
Validation criteria for enhanced fuzzy clustering,
PRL(29), No. 1, 15 January 2008, pp. 97-108.
WWW Version.
0711Supervised clustering; Fuzzy clustering; Cluster validity index;
Fuzzy functions
BibRef
Lu, Y.[Yu],
Fan, X.L.[Xi-Lu],
Fuzzy-weighted distance and its applications in pattern recognition and
classification,
ICPR88(II: 1065-1067).
WWW Version.
8811
BibRef
Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Fuzzy Clustering, Overview, Summary, Comparisons .