• Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Metaheuristic Clustering

Metaheuristic Clustering

Paperback

Series: Studies in Computational Intelligence, Book 178

Technology & EngineeringGeneral ComputersGeneral Mathematics

ISBN10: 3642100716
ISBN13: 9783642100710
Publisher: Springer Nature
Published: Oct 28 2010
Pages: 252
Weight: 0.85
Height: 0.57 Width: 6.14 Depth: 9.21
Language: English

Cluster analysis means the organization of an unlabeled collection of objects or patterns into separate groups based on their similarity. The task of computerized data clustering has been approached from diverse domains of knowledge like graph theory, multivariate analysis, neural networks, fuzzy set theory, and so on. Clustering is often described as an unsupervised learning method but most of the traditional algorithms require a prior specification of the number of clusters in the data for guiding the partitioning process, thus making it not completely unsupervised. Modern data mining tools that predict future trends and behaviors for allowing businesses to make proactive and knowledge-driven decisions, demand fast and fully automatic clustering of very large datasets with minimal or no user intervention.

Also in

General Computers