An Improvement in K-mean Clustering Algorithm Using Better Time and Accuracy

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Provided by: Academy & Industry Research Collaboration Center
Topic: Data Management
Format: PDF
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 partitioned into K clusters and the data are randomly choose to the clusters resulting in clusters that have the same number of data set.
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