In data mining, k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results in a partitioning of the data space into Vo

Using this set up we can even pause the insertion of metrics into the main cluster (in the event of a problem, or maintenance) with minimal impact to the user – alerts are processed separately so the user would only notice graphs no-longer updating.

This paper presents a new cluster validity index for nding a suitable number of fuzzy clusters with crisp and fuzzy data. The new index, called the ECAS-index, contains exponential compactness and separation measures. These measures indicate ho

LEACH [1] is an autonomous adaptive clustering protocol that distributes the energy load evenly among the sensors in the network using randomization. The nodes organize themselves into local clusters, with one node acting as the local base stat

word document for secure cluster