K-medoids

Known as: K-medoid, Partitioning Around Medoids 
The k-medoids algorithm is a clustering algorithm related to the k-means algorithm and the medoidshift algorithm. Both the k-means and k-medoids… (More)
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Topic mentions per year

Topic mentions per year

1995-2018
010203019952018

Papers overview

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2016
2016
k-medoids algorithm is a partitional, centroid-based clustering algorithm which uses pairwise distances of data points and tries… (More)
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2014
2014
Face recognition is one of the most unobtrusive biometric techniques that can be used for access control as well as surveillance… (More)
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2013
2013
Clustering is one of the data analysis methods that are widely used in data mining. In this method, we partitioned the data into… (More)
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2011
2011
K-medoids is a well known and widely used algorithm in data clustering. Performance of the algorithm depends on the… (More)
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2011
2011
  • Raghuvira Pratap
  • 2011
Clustering is the process of classifying objects into different groups by partitioning sets of data into a series of subsets… (More)
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Highly Cited
2009
Highly Cited
2009
This paper proposes a new algorithm for K-medoids clustering which runs like the K-means algorithm and tests several methods for… (More)
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2009
2009
This paper proposes a medoid based variation of rough K-means algorithm. The variation can be especially useful for a more… (More)
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2006
2006
Clustering analysis is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their… (More)
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2002
2002
In this paper a number of improvements are suggested that can be applied to most k-medoids-based algorithms. These can be divided… (More)
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Highly Cited
1999
Highly Cited
1999
This paper presents new algorithms (fuzzy e-methods (FCMdd) and fuzzy c trimmed medoids (FCTMdd)) for fuzzy clustering of… (More)
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