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Significance of Gender in Badminton Lunge Classification

机译:性别在羽毛球弓步分类中的意义

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摘要

Most badminton lunge studies considered only the male players. No study has investigated the effect of gender on the badminton lunge movement. Past researches presented the statistical analysis approach on badminton lunge motion study. However, no study has classified lunge motion specifically by gender segregation. This paper investigates the gender effects in distinguishing the five lunge directions; center-forward (CF), left-forward (LF), right-forward (PvF), left-lateral (L) and right-lateral (R) lunges using classification approach. The case study involved video captures of five-male and six-female university-level players lunging in the badminton 21-point singles. A total of 23 attributes of 10894 instances were extracted to classify lunges into CF, LF, RF, L and R lunges using 21 classification algorithms of the WEKA tool. Lunge direction classifications were performed on unsegregated and segregated genders datasets. Lunge classification on segregated gender datasets showed improvement over the unsegregated gender on 17 out of 21 classification algorithms. The notable improvements were on Trees-Hoeffding Tree (+8.67% on male, +3.08% on female) and Functions-Multilayer Perceptron algorithms (+4.35% on male, +9.37% on female). The study shows that gender segregation improves the lunge classification accuracies.
机译:大多数羽毛球弓步研究只考虑了男球员。没有研究调查了性别对羽毛球弓步运动的影响。过去的研究介绍了羽毛球弓步运动研究的统计分析方法。然而,没有学习的弓步运动明确通过性别分离。本文调查了区分五个弓步方向的性别效应;使用分类方法,中锋(CF),左前进(LF),右前进(PVF),左侧(L)和右侧(R)肺部。案例研究涉及五名男性和六年大学的视频捕获在羽毛球21点单打中刺激。提取总共23个属性10894个实例,使用Weka工具的21个分类算法将血管分类为CF,LF,RF,L和R肺部。在联臂章和隔离的性别数据集上执行刺激方向分类。关于隔离性别数据集的弓步分类表明,在21个分类算法中的17个中,在17个中的联邦性别方面表现出改善。显着的改进是树木 - 霍夫特树(男性+ 8.67%,女性+ 3.08%)和函数 - Multidayer Perceptron算法(雄性+ 4.35%,女性+ 9.37%)。该研究表明,性别隔离提高了弓步分类准确性。

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