World Library  

Add to Book Shelf
Flag as Inappropriate
Email this Book

Feature Selection with Acquisition Cost for Optimizing Sensor System Design : Volume 4, Issue 7 (04/09/2006)

By Iswandy, K.

Click here to view

Book Id: WPLBN0003986214
Format Type: PDF Article :
File Size: Pages 7
Reproduction Date: 2015

Title: Feature Selection with Acquisition Cost for Optimizing Sensor System Design : Volume 4, Issue 7 (04/09/2006)  
Author: Iswandy, K.
Volume: Vol. 4, Issue 7
Language: English
Subject: Science, Advances, Radio
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


APA MLA Chicago

Koenig, A., & Iswandy, K. (2006). Feature Selection with Acquisition Cost for Optimizing Sensor System Design : Volume 4, Issue 7 (04/09/2006). Retrieved from

Description: Institute of Integrated Sensor Systems, University of Kaiserslautern, Erwin-Schroedinger-Str., 67663 Kaiserslautern, Germany. Selection of variables from large sets of measurements is a common problem of data analysis and signal processing in many disciplines. In engineering and sensor technology the design of recognition systems can be optimized by judicious choice of subsets of relevant features. In particular, the effort required for signal processing and sensor registration can be considerably reduced by efficient feature selection. However, the current approaches in majority only consider the contribution of features or measurements to the classification ability of the system. The associated cost in terms of computation effort, the required electronics, and power dissipation is not explicitly in consideration. This paper proposes a multi-objective extension of feature selection including acquisition cost and employing and comparing two evolutionary optimization methods. The genetic and particle swarm algorithms and the results achieved with selected data sets will be presented. The results show, that particle swarm algorithm can select best features with lower cost and achieve more competitive results with regard to convergence time and classification accuracy than genetic algorithm.

Feature selection with acquisition cost for optimizing sensor system design

Agrafiotis, D K. and Cedeno, W J.: Feature Selection for Structure - Activitiy Correlation Using Binary Particle Swarms, J. Med. Chem., 45, 1098–1107, 2002; Aha, D W.: Feature Weighting for Lazy Learning Algorithms, edited by: Liu and Motoda, Kluwer Acad. Publ., 13–29, 1998.; Goldberg, D E.: Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley Publishing Comp. Inc., 1989.; Iswandy, K., Koenig, A., Fricke, T., Baumbach, M., and Schuetze, A.: Towards Automated Configuration of Multi-Sensor Systems Using Evolutionary Computation - A Method and a Case Study, J. Comput. and Theor. Nanoscience, 2, 574–582, 2005.; Jain, A. and Zongker, D.: Feature Selection: Evaluation, application, and small sample performance, IEEE Trans. on Pattern Analysis and Machine Intelligence, 19, 153–158, 1997.; Jain, A., Duin, R. and Mao, J.: Statistical Pattern Recognition: a Review, IEEE Trans. on Pattern Analysis and Machine Intelligence, 22, 4–37, 2000.; Kennedy, J. and Eberhart, R C.: Particle Swarm Optimization, in Proc. of IEEE Int. Conf. on Neural Networks (ICNN), 4, 1942–1948, 1995.; Kennedy, J. and Eberhart, R C.: A Discrete Binary Version of The Particle Swarm Algorithm, Proc. of Conf. on System, Man, and Cybernetics, 4104–4109, 1997.; Koenig, A.: A Novel Supervised Dimensionality Reduction Technique by Feature Weighting for Improved Neural Network Classifier Learning and Generalization, in Proc. of the 6th Int. Conf. on Soft-Computing and Information/Intelligent Systems IIZUKA�2000, Iizuka, Fukuoka, Japan, October, 746–753, 2000.; Koenig, A.: Dimensionality Reduction Techniques for Interactive Visualization, Exploratory Data Analysis, and Classification, in: Pattern Recognition in Soft Computing Paradigm, World Scientific, FLSI Soft Comp. Series, edited by Pal,~N R., 2, 1–37, 2001.; Koenig, A. and Gratz, A.: Advanced Methods for the Analysis of Semiconductor Manufacturing Process Data, in: Advanced Techniques in Knowledge Discovery and Data Mining, edited by Pal,~N R. and Jain,~L C., Springer Verlag, 27–74, 2005.; Langley, P.: Elements of Machine Learning, Morgan Kaufmann Publishers, 1996.; Koenig, A., Mayr, C., Bormann, T. and Klug, C.: Dedicated Implementation of Embedded Vision Systems Employing Low-Power Massively Parallel Feature Computation, in: Proc. of the 3rd VIVA-Workshop on Low-Power Information Processing, Chemnitz, Germany, 1–8, 2002.; Kohavi, R. and John, G H.: The Wrapper Approach, in: Feature Extraction, Construction and Selection, edited by Liu and Motoda, Kluwer Academic Publishers, 33–50, 1998.; Mao, K Z.: Fast Orthogonal Forward Selection, IEEE Trans. on Neural Networks, 13, 1218–1224, 2002.; Paclík, P., Duin, R P W., van Kempen, G M P., and Kohlus, R.: On Feature Selection with Measurement Cost and Grouped Features, edited by Caelli~T. et al.: SSPR and SPR 2002, LNCS 2396, Springer-Verlag, 461–469, 2002.\vadjust; Siedlecki, W. and Sklansky, J.: On Automatic Feature Selection, Int. J. Pattern Recognition, 2, 197–220, 1988.; Siedlecki, W. and Sklansky, J.: A Note on Genetic Algorithm for Large Scale Feature Selection, Pattern Recognition Lett., 10, 335–347, 1989.; Yang, J. and Honavar, V.: Feature subset selection using a genetic algorithm, in: Feature Extraction, Construction and Selection, edited by Liu and Motoda, Kluwer Academic Publishers, 117–136, 1998.; Zitzler, E. and Thiele, L.: Multiobjective Evolutionary Algorithms: a Comparative Case Study and the Strength Pareto Approach, IEEE Trans. on Evolutionary Computation, 3(4), 257–271, 1999.


Click To View

Additional Books

  • Modeling of Temperature Scenarios in a M... (by )
  • Quantitative Design Space Exploration of... (by )
  • The Role of Surface Fluxes in the Develo... (by )
  • An Integrated 3.1–5.1 Ghz Pulse Generato... (by )
  • Design and Realization of a Broadband Si... (by )
  • Mos Capacitances Used in Mixed-signal Ci... (by )
  • Megapoli: Concept of Multi-scale Modelli... (by )
  • A Multi Channel Coupling Based Approach ... (by )
  • Entwurfskonzept Einer Car2Car-multiband-... (by )
  • On the Predictability of Outliers in Ens... (by )
  • Performance Analysis of General Purpose ... (by )
  • Continuous Measurements of Near Surface ... (by )
Scroll Left
Scroll Right


Copyright © World Library Foundation. All rights reserved. eBooks from World eBook Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.