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Prediction of the admission lines of college entrance examination based on machine learning

机译：基于机器学习的高考录取线预测

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摘要

Accurate prediction to college entrance examination(CEE) results is very important for the candidates to fill in the application and the relevant analysis of the CEE. At present, the prediction of CEE scores is based on data statistics, probability model and some weighted combination models. Since generating the model for predicting college admission lines uses too little reference factor, and the error is relatively large, so the reference value is very small. In this paper, machine learning methods are used to carry out the college admission lines of research and prediction. Specially, in this paper Adaboost algorithm is used to study and forecast, which belongs to ensemble learning. Finally, the result of this model is given, which is better than the current prediction method.
机译：对于高考成绩的准确预测，对于考生填写申请材料和进行相关分析非常重要。目前，CEE分数的预测是基于数据统计，概率模型和一些加权组合模型的。由于生成用于预测大学录取线的模型使用的参考因子太小，并且误差相对较大，因此参考值非常小。在本文中，机器学习方法被用于进行大学入学线的研究和预测。特别地，本文将Adaboost算法用于学习和预测，属于集成学习。最后，给出了该模型的结果，优于当前的预测方法。

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