Comparison of Classification Methods for Golf Putting Performance Analysis

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1 Page 1 of 5 Look Find out Inside how Get to Access access preview-only content Computational Intelligence and Decision Making Intelligent Systems, Control and Automation: Science and Engineering Volume 61, 2013, pp Comparison of Classification Methods for Golf Putting Performance Analysis Abstract This paper presents a comparative case study on the classification accuracy between five methods for golf putting performance analysis. In a previous work, a digital camera was used to capture 30 trials of 6 expert golf players. The detection of the horizontal position of the golf club was performed using a computer vision technique followed by the estimation algorithm Darwinian Particle Swarm Optimization (DPSO) in order to obtain a kinematical model of each trial. In this paper, the estimated parameters of the models are used as sample and training data of five classification algorithms: (1) Linear Discriminant Analysis (LDA); (2) Quadratic Discriminant Analysis (QDA); (3) Naïve Bayes with Normal (Gaussian) distribution (NV); (4) Naïve Bayes with Kernel Smoothing Density Estimate (NVK) and (5) Least Squares Support Vector Machines with Radial Basis Function Kernel (LS-SVM). The five classification methods are then compared through the analysis of the confusion matrix and the area under the Receiver Operating Characteristic curve (AUC). Within this Chapter Introduction Survey of Classification Methods Experimental Results Conclusions References

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3 Page 3 of 5 Related Content References (20) About this Chapter Title Comparison of Classification Methods for Golf Putting Performance Analysis Book Title Computational Intelligence and Decision Making Book Subtitle Trends and Applications Pages pp Copyright 2013 DOI / _4 Print ISBN Online ISBN Series Title Intelligent Systems, Control and Automation: Science and Engineering Series Volume 61 Series ISSN Publisher Springer Netherlands Copyright Holder Springer Science+Business Media Dordrecht Additional Links Topics Industry Sectors ebook Packages About this Book Computational Intelligence Artificial Intelligence (incl. Robotics) Information Systems Applications (incl. Internet) Electronics Telecommunications IT & Software

4 Page 4 of 5 ebook Package english full Collection ebook Package english Engineering Editors Ana Madureira Cecilia Reis (ID5) (ID4) Viriato Marques (ID6) Editor Affiliations Authors ID4. Computer Science Department, Polytechnique Institute of Porto ID5. Electrical and Engineering Department, Polytechnique Institute of Porto ID6., Department of Computer Science and Syste, Polytechnique Institute of Coimbra J. Miguel A. Luz (1) Micael S. Couceiro (1) David Portugal (2) Rui P. Rocha (2) Author Affiliations Continue reading... Hélder Araújo (2) Gonçalo Dias (3) 1. RoboCorp, Department of Electrical Engineering (DEE), Engineering Institute of Coimbra (ISEC), Coimbra, Portugal 2. Institute of Systems and Robotics (ISR), University of Coimbra (FCTUC), Coimbra, Portugal 3. RoboCorp, Faculty of Sport Sciences and Physical Education, University of Coimbra (FCDEF), Coimbra, Portugal To view the rest of this content please follow the download PDF link above scientific documents at your fingertips Springer, Part of Springer Science+Business Media

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