Swarm Intelligence and Bio-Inspired Computation: 18. Opportunities and Challenges of Integrating Bio-Inspired Optimization and Data Mining Algorithms
Book Details
Author(s)Simon Fong
PublisherElsevier
ISBN / ASINB019ZU2LGQ
ISBN-13978B019ZU2LG4
Sales Rank99,999,999
MarketplaceUnited States 🇺🇸
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.
