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Cluster
analysis
or
clustering
is the task of grouping a set of objects in such a way that objects in the same
group (called a
cluster
) are more similar (in some sense or another) to each other than to those in other
groups (clusters)
.
K

means
is
one of the simplest unsupervised learning algorithms that solve the well
known clustering problem.
The
process of k means algorithm data
is partiti
oned int
o K clusters and the
data are randomly choose
to the clusters resulti
ng in clusters that have
the sa
me number of data
set
.
This
paper is proposed a new K means clustering algorithm we calculate the initial
centroids
systemically
instead of random assigned due to which accuracy and time
improved.
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