新高考“6选3”模式下预测高校录取分数的方法

Method on Predicting College Admission Score in the“Three out of Six”Model of New College Entrance Examination

由于新高考“6选3”模式不再区分文理科,这使得无法根据院校历史文理分科数据对新高考院校录取分数进行有效预测。鉴于此,提出了一种文理科历史数据归一化方案,以招生人数作为权重将院校文理分科历史数据合并生成虚拟数据,并使用线性回归模型对新高考“6选3”模式下高校录取分数做出预测。实验结果表明,该方法能够整合历史文理分科数据,对实施新高考模式高校的录取分数进行精准预测。

Because the“three out of six”model of the new college entrance examination no longer distinguishes liberal arts and sciences,it is impossible to effectively predict the admission scores of the new college entrance examination colleges according to the historical data of liberal arts and sciences of colleges.In view of this,this paper proposes a normalization scheme for the historical data of liberal arts and sciences,which combines the historical data of liberal arts and sciences of colleges and generates virtual data with the enrollment number as the weight,and uses the linear regression model to predict the admission scores of colleges under the“three out of six”model of the new college entrance examination.The experimental results show that this method can integrate the historical data of liberal arts and sciences,and accurately predict the admission scores of colleges implementing the new college entrance examination model.