Computational Intelligence in Data Mining - Volume 1

Computational Intelligence in Data Mining - Volume 1

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The contributed volume aims to explicate and address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizationsa€™ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.0.0296 Error plot Exchange Rate using FLANN with LMS 0.0294 0.0292 0.029 0.0288 0.0286 0.0284 0.0282 0.028 0 ... 5 Conclusion FOREX rate prediction has been a real challenging problem due to the volatile nature of the FOREX market. ... Harvey, A.C.: Forecasting structural time series models and the Kalman filter.


Title:Computational Intelligence in Data Mining - Volume 1
Author: Lakhmi C. Jain, Behera H.S., Jyotsna Kumar Mandal, Durga Prasad Mohapatra
Publisher:Springer - 2014-12-10
ISBN-13:

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