Synthetic Evaluation Method Based Support Vector Classifier and Regression Machine
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摘要: 采用支持向量多值分类机和回归机进行综合评价排序,以提高机器学习方法的综合评价排序能力,并以管理信息系统综合评价为例,与人工神经网络(ANN)方法进行了对比研究.试验结果表明,基于支持向量多值分类机综合评价得分之间的差异比ANN更明显,而且基于支持向量回归机综合评价得分的相对误差明显小于ANN.Abstract: To improve the synthetic evaluation and ranking abilities of machine learning methods,a support vector multi-classifier and a support vector regression machine were applied to the ranking of synthetic evaluation.By taking the evaluation of a management information system as an example,a contrast research between the proposed approach and ANN(artificial neural network) was made.Experimental results show that the difference of synthetic evaluation scores obtained by a support vector multi-classifier is more remarkable than that by ANN,and the relative error of synthetic evaluation scores based on a support vector regression machine is smaller than that based on ANN.
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