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A Wine Consumption Prediction Model Based on L-DAGLSSVM

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Recent Developments in Data Science and Business Analytics

Part of the book series: Springer Proceedings in Business and Economics ((SPBE))

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.

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Wang, X., Lu, S., Zhou, Z. (2018). A Wine Consumption Prediction Model Based on L-DAGLSSVM. In: Tavana, M., Patnaik, S. (eds) Recent Developments in Data Science and Business Analytics. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-72745-5_35

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