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A Decision Support System of Selecting Groups (Science/ Business Studies/ Humanities) for Secondary School Students in Bangladesh

机译:孟加拉国中学生选拔小组(科学/商业/人文科学)的决策支持系统

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As education is the only way to turn a person into human resource, every country tries to give her citizens proper scope of bringing out their inner ability by offering the appropriate education. According to the education system of Bangladesh, an 8th grade completing student has to choose a group (science, Business Studies, humanity) for further studies. This group will be his/her initial highway for higher education. But it is a matter of sorrow that, in Bangladesh this crucial event is done by some rumors and some traditional old school ways, which are mostly wrong and destructive. From the perspective of this country, the only way of choosing those groups is previous result. Of course, result is one of the most important attribute, but it should not be the only thing. Again in this country, Science is thought to be superior than other groups. That's why, parents have the tendency to impose this group to their children without knowing their ability and interest and leads them towards an uncertain future. Therefore, the aim of this paper is to build a model of group selection by analyzing some random attributes of higher level students who have already gone through this event of selecting groups with the help of data mining and some machine learning algorithms, so that a newly 9th grade student could have the proper direction of selecting a group which is best for him/her. For the purpose of experimentation we have used three machine learning algorithms: Naïve Bayes, Sequential Minimal Optimization (SMO) and Random Forest. Among these algorithms Random forest gives the best prediction result with an accuracy of 84.9%.
机译:由于教育是将人转化为人力资源的唯一途径,每个国家都试图通过提供适当的教育来赋予其公民适当的能力,以发挥其内在能力。根据孟加拉国的教育系统,有8 年级完成的学生必须选择一个小组(科学,商业研究,人文科学)进行进一步研究。该小组将是他/她接受高等教育的最初途径。但是,令人遗憾的是,在孟加拉国,这一至关重要的事件是由一些谣言和一些传统的守旧派做法造成的,这些谣言和某些传统的守旧派做法大都是错误和破坏性的。从这个国家的角度来看,选择这些群体的唯一方法就是先前的结果。当然,结果是最重要的属性之一,但并不是唯一的结果。同样在这个国家,科学被认为比其他组织优越。因此,父母倾向于在不知道自己的能力和兴趣的情况下将这个群体强加给他们的孩子,并导致他们走向不确定的未来。因此,本文的目的是通过借助数据挖掘和一些机器学习算法分析已经经历过选拔活动的高年级学生的一些随机属性,来建立一个选拔模型。 9 一年级的学生可以有一个正确的方向来选择最适合他/她的小组。为了进行实验,我们使用了三种机器学习算法:朴素贝叶斯,顺序最小优化(SMO)和随机森林。在这些算法中,随机森林以84.9%的准确度提供了最佳的预测结果。

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