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A Wine Consumption Prediction Model Based on L-DAGLSSVM

In: Recent Developments in Data Science and Business Analytics

Author

Listed:
  • Xiao Wang

    (College of Science, China Agricultural University)

  • Sijie Lu

    (College of Science, China Agricultural University)

  • Zhijian Zhou

    (College of Science, China Agricultural University)

Abstract

With the increasing demand of wine consumption, the marketing of wine consumption is expanding. In this paper, we do a research about the decision behavior of Chinese wine consumers in order to grasp the consumption demand of wine at different prices better. We acquire 774 questionnaires finally, and the 528 of which are valid. According to the consumption prices, we divide wine consumers into three types. Then we propose a multi-class classification method named L-DAGLSSVM for constructing prediction model of consumption types, which is based on LDA and the directed acyclic graph least squares support vector machine (DAGLSSVM). The numerical experiments demonstrate that our algorithm gains better performance compared with other algorithms. And the prediction model plays an important role in commercial fields that it can provide an effective reference for the wine production, purchase and marketing strategies etc.

Suggested Citation

  • Xiao Wang & Sijie Lu & Zhijian Zhou, 2018. "A Wine Consumption Prediction Model Based on L-DAGLSSVM," Springer Proceedings in Business and Economics, in: Madjid Tavana & Srikanta Patnaik (ed.), Recent Developments in Data Science and Business Analytics, chapter 0, pages 321-326, Springer.
    • Handle: RePEc:spr:prbchp:978-3-319-72745-5_35
    DOI: 10.1007/978-3-319-72745-5_35
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