Browsing Department of Computer Science and Information Systems by Subject "Parallel framework"

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Parallel Framework for Efficient k-means Clustering

Goyal, Navneet; Goyal, Poonam (ACM Digital Library, 2015-10)

Handling and processing of larger volume of data requires efficient data mining algorithms. k-means is a very popular clustering algorithm for data mining, but its performance suffers because of initial seeding problem. ...
A Parallel Framework for Grid-Based Bottom-Up Subspace Clustering

Goyal, Navneet; Goyal, Poonam (IEEE, 2016)

Clustering is a popular data mining and machine learning technique which discovers interesting patterns from unlabeled data by grouping similar objects together. Clustering high-dimensional data is a challenging task as ...

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