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  • Search: subject:"Classifier Design and Evaluation"
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Year of publication
Subject
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Classifier Design and Evaluation 1 Face and gesture recognition 1 Genetic Search 1 Kernel Function 1 Non-Linear Support Vector Machines 1 Radial Basis Function 1 SMO Platt’s Algorithm 1 Soft Margin SVM 1 classifier design and evaluation 1 customer relationship management (CRM) 1 data mining methods and algorithms 1 discriminant analysis 1 feature evaluation and selection 1 multiclass classifier design and evaluation 1 nonparametric 1 pattern recognition 1
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Online availability
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Free 3
Type of publication
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Article 2 Book / Working Paper 1
Language
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English 2 Undetermined 1
Author
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COCIANU, Catalina 1 Li, Zhifeng 1 Lin, Dahua 1 POEL, D. VAN DEN 1 PRINZIE, A. 1 STATE, Luminita 1 Tang, Xiaoou 1 USCATU, Cristian 1
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Institution
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Faculteit Economie en Bedrijfskunde, Universiteit Gent 1
Published in...
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Informatica Economica 1 Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 1
Source
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RePEc 2 BASE 1
Showing 1 - 3 of 3
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Alternative Strategies in Learning Nonlinear Soft Margin Support Vector Machines
COCIANU, Catalina; STATE, Luminita; USCATU, Cristian - In: Informatica Economica 18 (2014) 2, pp. 42-52
The aims of the paper are multifold, to propose a new method to determine a suitable value of the bias corresponding to the soft margin SVM classifier and to experimentally evaluate the quality of the found value against one of the standard expression of the bias computed in terms of the support...
Persistent link: https://www.econbiz.de/10011165701
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Nonparametric discriminant analysis for face recognition
Li, Zhifeng; Lin, Dahua; Tang, Xiaoou - 2008
In this paper, we develop a new framework for face recognition based on nonparametric discriminant analysis (NDA) and multi-classifier integration. Traditional LDA-based methods suffer a fundamental limitation originating from the parametric nature of scatter matrices, which are based on the...
Persistent link: https://www.econbiz.de/10009433068
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Random Forrests for Multiclass classification: Random Multinomial Logit
PRINZIE, A.; POEL, D. VAN DEN - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2007
Several supervised learning algorithms are suited to classify instances into a multiclass value space. MultiNomial Logit (MNL) is recognized as a robust classifier and is commonly applied within the CRM (Customer Relationship Management) domain. Unfortunately, to date, it is unable to handle...
Persistent link: https://www.econbiz.de/10004982843
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