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《Journal of Anhui Agricultural Sciences》 2008-35
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Research on the SVR-KNN Method Applied in the Herbicide QSAR

OU Wei-min et al(College of Vocational Technology & Trade of Guangdong,Guangzhou,Guangdong 510430)  
[Objective]An effective combination forecasting method for QSAR(QSAR) analysis was explored.[Method] The combination forecasting method of SVR and KNN was presented.The optimal selection was based on the mean square error(MSE) and the SVR was optimally screened based on the kernel function.Based on the most optimal kernel function,the selection was done according to SVR descriptor and the descriptor was reserved.The impacting extent of the reservation descriptors on the accuracy of forecasting was explained with "The enforcement law of the last one being out".The quality of sample was reflected based on the different KNN forecast values and a sub-model was built,and finally,the combination forecasting was carried out based on the SVR.The QSAR model of the kinds of herbicide such as sulfonylurea,triazolo and pyrimidine sulfonamide was established with combination forecasting method.[Result] The modeling results showed that the forecasting method based on the combination of SVR and KNN was the most accurate in all of models,with smallest risk in the structure and non-linear,and also,it can effectively overcome the over-fit,and with the advantage such as good generalization ability etc.[Conclusion] The forecasting method based on the combination of SVR and KNN had many advantages,which can be widely applied in study on the QSAR.
【Fund】: 湖南省科学计划一般项目(2008SK3056)
【CateGory Index】: S482.4
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