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1 – 2 of 2Jianxiang Qiu, Jialiang Xie, Dongxiao Zhang and Ruping Zhang
Twin support vector machine (TSVM) is an effective machine learning technique. However, the TSVM model does not consider the influence of different data samples on the optimal…
Abstract
Purpose
Twin support vector machine (TSVM) is an effective machine learning technique. However, the TSVM model does not consider the influence of different data samples on the optimal hyperplane, which results in its sensitivity to noise. To solve this problem, this study proposes a twin support vector machine model based on fuzzy systems (FSTSVM).
Design/methodology/approach
This study designs an effective fuzzy membership assignment strategy based on fuzzy systems. It describes the relationship between the three inputs and the fuzzy membership of the sample by defining fuzzy inference rules and then exports the fuzzy membership of the sample. Combining this strategy with TSVM, the FSTSVM is proposed. Moreover, to speed up the model training, this study employs a coordinate descent strategy with shrinking by active set. To evaluate the performance of FSTSVM, this study conducts experiments designed on artificial data sets and UCI data sets.
Findings
The experimental results affirm the effectiveness of FSTSVM in addressing binary classification problems with noise, demonstrating its superior robustness and generalization performance compared to existing learning models. This can be attributed to the proposed fuzzy membership assignment strategy based on fuzzy systems, which effectively mitigates the adverse effects of noise.
Originality/value
This study designs a fuzzy membership assignment strategy based on fuzzy systems that effectively reduces the negative impact caused by noise and then proposes the noise-robust FSTSVM model. Moreover, the model employs a coordinate descent strategy with shrinking by active set to accelerate the training speed of the model.
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Keywords
Liangjun Zhou, Jerred Junqi Wang, Xiaoying Chen, Chundong Lei, James J. Zhang and Xiao Meng
Building upon the framework of glocalization, the purpose of this paper is to summarize the development of National Basketball Association (NBA) in Chinese market, explore its…
Abstract
Purpose
Building upon the framework of glocalization, the purpose of this paper is to summarize the development of National Basketball Association (NBA) in Chinese market, explore its successful and unsuccessful places, and propose strategies of glocalization for the NBA as well as other overseas sport leagues.
Design/methodology/approach
The current case study was organized by summarizing the developmental history of NBA in China, analyzing its current promotional practices, investigating into its marketing strategies, and extrapolating practical references for other sport leagues aiming to penetrating into the Chinese marketplace.
Findings
The current case study concluded that when facing the current challenges, the NBA needs to bring authentic American cultural commodities while adding Chinese characteristics to accommodate local fans. Meanwhile, the NBA management needs to continue seeking ways to work out and through the differences in government models and cultural contexts between China and USA. In addition, this study suggested that the research framework of glocalization would be an ever intriguing inquiry needed for other sport organizations or leagues seeking expansion to overseas markets.
Originality/value
A thorough case study with the NBA that has achieved huge successes in Chinese markets will provide valuable implications for sport leagues to broaden their overseas markets.
Details