DocumentCode :
2616925
Title :
Noise clustering algorithm revisited
Author :
Davé, Rajesh N. ; Sen, Sumit
Author_Institution :
Dept. of Mech. Eng., New Jersey Inst. of Technol., Newark, NJ, USA
fYear :
1997
fDate :
21-24 Sep 1997
Firstpage :
199
Lastpage :
204
Abstract :
Dave´s (1991) noise clustering (NC) algorithm is revisited. In the original NC algorithm, the distance of a noise prototype from all the points was defined to be a constant value δ. While this idea works well in detecting a variety of cluster shapes in noisy data, use of the same constant value of δ makes NC somewhat limited in its scope. The authors allow S to take different values for different feature vectors, and find interesting results due to this modification. It is shown that the membership generated by NC algorithm is a product of two terms, one is the original fuzzy c-means (FCM) membership responsible for data partitioning, and the other is a robust M-estimator type weight (or like a generalized possibilistic membership) that achieves a mode seeking effect, and imparts robustness. In this light, it is shown that the NC technique is a generalization of the possibilistic clustering technique. An interesting fact about the robust component of the NC membership is regarding the appearance of term related to the harmonic mean distance of a point from all the classes. The role of this term is discussed along with other possible generalizations, including one that makes the generalized NC a fuzzy c-class extension of robust M-estimators
Keywords :
algorithm theory; data handling; fuzzy logic; noise; possibility theory; cluster shapes; data partitioning; feature vectors; fuzzy c-means membership; harmonic mean distance; mode seeking effect; noise clustering algorith; noisy data; possibilistic clustering technique; robust M-estimator type weight; robustness; Clustering algorithms; Data visualization; Mechanical engineering; Noise robustness; Noise shaping; Partitioning algorithms; Prototypes; Shape; Switches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Information Processing Society, 1997. NAFIPS '97., 1997 Annual Meeting of the North American
Conference_Location :
Syracuse, NY
Print_ISBN :
0-7803-4078-7
Type :
conf
DOI :
10.1109/NAFIPS.1997.624037
Filename :
624037
Link To Document :
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