… in the natural classes of data [45]. The standard K-means algorithm clusters the data based
on the properties of the data shared among the data objects, which naturally results in crisp …

… The K-Means clustering method is one of the data mining methods that is non-hierarchical
clustering that groups data in the form of one or more clusters. Data that have the same …

… The clustering algorithms come with their own set of chal… of data and the mechanism
adopted to form clusters, we mention certain drawbacks incurred by various clustering algorithms: …

… distance from any member of one cluster to any member of the other cluster. The complete-linkage
algorithm clusters are more compact and tightly bound than single-linkage clustering (…

… FCM algorithm to make it applicable to data with unequal cluster … Revised FCM (RFCM)
algorithm employs adaptive … the cluster centers and modifies constraint of the FCM algorithm to …

… In order to test whether the IK-means algorithm is capable of cluster data of any shape or not…
-means algorithm can cluster data of any shape, including spherical and non-spherical data. …

… the CPSO based clustering algorithm. In this study, an attempt has been made … cluster the
particles through similarity in data clustering. Among those clusters of particles, each cluster's …

… In this paper, we construct an unsupervised learning schema for the k-means algorithm so
… clusters. That is, we propose a novel unsupervised k-means (Ukmeans) clustering algorithm …

… Most of the experts interviewed in this book are calling for more data-efficient algorithms.
For instance, Oren Etzioni quoted in the book that “stepping stone [towards AGI] is that it’s very …

… In this paper Authors give an overview of nature inspired metaheuristic algorithms for
partitional clustering. According to the author the old gradient based partitional clustering were …