cluster point

cluster point

[′kləs·tər ‚pȯint]
(mathematics)
A cluster point of a set in a topological space is a point p whose neighborhoods all contain at least one point of the set other than p. Also known as accumulation point; limit point.
References in periodicals archive ?
In [6] Fridy introduced the concept of statistical limit point and statistical cluster point of real sequences and gave some properties of the corresponding sets.
Globally, we have sought to drive this programme as a cluster point for innovative transnational cooperation and best practice.
This observation, on the other hand, indicates a slight overall shift towards AKP from a cluster point of view in the 2011 elections when compared to the overall political landscape between 1999 and 2009.
In [16], Fridy introduced the definitions of statistical limit point and statistical cluster point and using classical techniques, established some basic results.
It may be in the form of localities being made to come closer through the pull effect of facilities and services concentrated at the cluster point (physical) or the increased interaction between the small villages a the cluster point by way of services and facilities.
During this, more than 95% of skin pixels are classified using RGB model, more than 80% of skin pixels are classified using k-means under initial cluster point method and more than 85% of skin pixels are classified using distance metric method.
We approach cloud servers from a cluster point of view providing users with greater management options over their assets," said John Keagy, CEO, GoGrid.
The cluster point with maximum number of the start '5' and end points d are computed based on the linkage information.
0] [member of] H, every weak cluster point of the sequence [x.
n]} has a cluster point in X (this definition is equivalent to that given in [18, Definition]).
But they do not mention any neighboring cluster points inside a specified threshold.
K-means clustering can be used on large data sets and functions by assigning points to clusters and recalculating cluster points in order to divide data into sets that can be more thoroughly analyzed.

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