Swarm Intelligence and Bio-Inspired Computation: 18. Opportunities and Challenges of Integrating Bio-Inspired Optimization and Data Mining Algorithms

Swarm Intelligence and Bio-Inspired Computation: 18. Opportunities and Challenges of Integrating Bio-Inspired Optimization and Data Mining Algorithms
ISBN-10
012806904X
ISBN-13
9780128069042
Series
Swarm Intelligence and Bio-Inspired Computation
Category
Computers
Pages
450
Language
English
Published
2013-05-16
Publisher
Elsevier Inc. Chapters
Author
Simon Fong

Description

Data mining has evolved from methods of simple statistical analysis to complex pattern recognition in the past decades. During the progression, the data mining algorithms are modified or extended in order to overcome some specific problems. This chapter discusses about the prospects of improving data mining algorithms by integrating bio-inspired optimization, which has lately captivated much of researchers’ attention. In particular, high dimensionality and the unavailability of the whole data set (as in stream mining) in the training data have known to be two major challenges. We demonstrated that these two challenges, through two small examples such as K-means clustering and time-series classification, can be overcome by integrating data mining and bio-inspired algorithms.

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