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An Ensemble Method for Medicine Best Selling Prediction

机译:药物最畅销预测的综合方法

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In this paper the author presents a data mining model based ensemble methodology in medicine selling prediction. The ANN algorithm is utilized for feature selection, and some machine learning techniques are constructed for ensemble model in medicine best selling and best sell season prediction. The verification is conducted on the real cases from GuiYang ZhiFuTang Pharmacy Company Sell data which consists of 63044 records and 17 fields. The real case experiments show that, our approach works effectively and could be used as an assistant approach for selling analysis in some circumstances.
机译:在本文中,作者提出了一种基于数据挖掘模型的集成方法,用于药物销售预测。利用神经网络算法进行特征选择,并为医学畅销书和畅销书季节预测中的集成模型构建了一些机器学习技术。对贵阳市芝Y堂药房公司销售数据的真实案例进行了验证,该数据包括63044个记录和17个字段。实际案例实验表明,我们的方法行之有效,在某些情况下可以用作销售分析的辅助方法。

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