| 基于Clementine的毛细管电泳数据挖掘方法研究 |
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| 引用本文： | 刘硕,董鸿晔.基于Clementine的毛细管电泳数据挖掘方法研究[J].计算机与现代化,2011(5):131-134. |
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| 作者姓名： | 刘硕 董鸿晔 |
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| 作者单位： | 1. 沈阳药科大学药学院,辽宁,沈阳110016
2. 沈阳药科大学基础学院,辽宁,沈阳,110016 |
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| 基金项目： | 国家自然科学基金重大研究计划项目(90612002); 辽宁省教育厅高等学校科学研究项目(05L426) |
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| 摘 要： | 为预测毛细管电泳迁移时间,利用数据挖掘软件Clementine的神经网络模型对维生素B1等7种药物的350个迁移时间数据进行预测,对于药物的50组数据,取49组作为学习集(或称训练集)进行训练,然后用训练好的网络对剩下的1组进行预测。Clementine的预测结果相对误差大部分小于10%,预测结果比较准确,对于大样本数据利用数据挖掘中的神经网络模型进行预测会得到比较好的结果。
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| 关 键 词： | 数据挖掘 神经网络 药学 |
Data Mining Based on Clementine Applied in Capillary Electrophoresis |
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| LIU Shuo,DONG Hong-ye.Data Mining Based on Clementine Applied in Capillary Electrophoresis[J].Computer and Modernization,2011(5):131-134. |
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| Authors: | LIU Shuo DONG Hong-ye |
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| Affiliation: | LIU Shuo1,DONG Hong-ye2(1.School of Pharmacy,Shenyang Pharmaceutical University,Shenyang 110016,China,2.School of Basic,China) |
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| Abstract: | To predict capillary electrophoresis mobility time,Clementine's neural network model is used to predict the electrophoresis mobility of 7 drugs of vitamin B1,etc.350,as the 50 sets of data for the drug,taken as learning set(or training set) of 49 groups for training,and then takes the 1 set of data as prediction set.The most of the prediction results of relative error of Clementine is less than 10%,the prediction result is more accurate,for large sample data using neural network model of data mining to pred... |
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| Keywords: | data mining neural network pharmacy |
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