DPM: Fast and scalable clustering algorithm for large scale high dimensional datasets

Ghanem, Tamer F.; Elkilani, Wail S.; Ahmed, Hatem; Hadhoud, Mohiy M.

doi:10.1109/icenco.2014.7050427

Search citation statements

Order By: Relevance

Paper Sections

Select...

Methods1

Previously Proposed Dpm Clustering Algorithm1

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2014

Publication Types

Select...

Other1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(3 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our experiments ran on a system with 3.0 GHz Intel® Core™ i5 processor, 4GB RAM and Windows 7 as an operating system. As proposed in [5], DPM is controlled by three insensitive parameters. This means that DPM results does not vary over a range of values for each of these parameters.…”

Section: Methodsmentioning

confidence: 99%

“…DPM is a fast clustering algorithm for large scale high dimension datasets with three steps as stated below [5].…”

Section: Previously Proposed Dpm Clustering Algorithmmentioning

confidence: 99%

“…Its detectors are shaped as hyper-spheres with radii thresholds to cover normal volumes. In another previous research [5], we proposed a fast clustering algorithm for large scale high dimensional dataset called Density Partitioning and Merging (DPM). Results shows its extreme fastness compared to other clustering algorithms.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations