103
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FUIN
2011
13 years 5 months ago
2011
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
FLAIRS
2007
14 years 4 months ago
2007
Clustering attempts to discover significant groups present in a data set. It is an unsupervised process. It is difficult to define when a clustering result is acceptable. Thus,...
CEC
2007
IEEE
14 years 8 months ago
2007
IEEE
—Identification of the correct number of clusters and the corresponding partitioning are two important considerations in clustering. In this paper, a newly developed point symme...
DEXAW
2009
IEEE
14 years 8 months ago
2009
IEEE
Abstract—The k-means method is a simple and fast clustering technique that exhibits the problem of specifying the optimal number of clusters preliminarily. We address the problem...
MCS
2010
Springer
14 years 8 months ago
2010
Springer
One of the challenges in unsupervised machine learning is finding the number of clusters in a dataset. Clustering Validity Indices (CVI) are popular tools used to address this pro...
SIGMOD
2002
ACM
15 years 1 months ago
2002
ACM
Clustering results validation is an important topic in the context of pattern recognition. We review approaches and systems in this context. In the first part of this paper we pre...