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  • Search: subject:"parameter-selection technique"
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Year of publication
Subject
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B-to-B-Marketing 1 B2B e-commerce 1 Beziehungsmarketing 1 Business-to-business marketing 1 Churn prediction modeling 1 E-commerce 1 Electronic Commerce 1 Forecasting model 1 Lieferantenmanagement 1 Marketing retention strategies 1 Mustererkennung 1 Parameter-selection technique 1 Pattern recognition 1 Prognoseverfahren 1 Relationship marketing 1 Supplier relationship management 1 Support vector machines 1 churn prediction 1 data mining 1 parameter-selection technique 1 subscription services 1 support vector machines 1
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Online availability
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Free 1 Undetermined 1
Type of publication
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Article 1 Book / Working Paper 1
Type of publication (narrower categories)
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Article in journal 1 Aufsatz in Zeitschrift 1
Language
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English 2
Author
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COUSSEMENT, K. 1 Gordini, Niccolò 1 POEL, D. VAN DEN 1 Veglio, Valerio 1
Institution
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Faculteit Economie en Bedrijfskunde, Universiteit Gent 1
Published in...
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Industrial marketing management : the international journal for industrial and high-tech firms 1 Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 1
Source
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ECONIS (ZBW) 1 RePEc 1
Showing 1 - 2 of 2
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Customers churn prediction and marketing retention strategies. An application of support vector machines based on the AUC parameter-selection technique in B2B e-commerce industry
Gordini, Niccolò; Veglio, Valerio - In: Industrial marketing management : the international … 62 (2017), pp. 100-107
Persistent link: https://www.econbiz.de/10011707072
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Cover Image
Churn Prediction in Subscription Services: an Application of Support Vector Machines While Comparing Two Parameter-Selection Techniques
COUSSEMENT, K.; POEL, D. VAN DEN - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2006
CRM gains increasing importance due to intensive competition and saturated markets. With the purpose of retaining customers, academics as well as practitioners find it crucial to build a churn prediction model that is as accurate as possible. This study applies support vector machines in a...
Persistent link: https://www.econbiz.de/10004983063
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