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计算机系统应用:2018,27(12):268-273
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基于粗糙集的慢性病变分级方法
胡建强, 王元
(厦门理工学院 计算机与信息工程学院, 厦门 361024)
Classification Method of Chronic Lesions Based on Rough Sets
HU Jian-Qiang, WANG Yuan
(School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China)
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投稿时间:2018-04-12    修订日期:2018-05-08
中文摘要: 由于云健康生理监测数据因具有时间连续性、非精确性、模糊性等特性,从而导致传统分类算法很难直接运用.针对上述问题,提出一种基于粗糙集的慢性病变分级方法.该方法首先采用融合相关度和Chi-merge统计量离散化生理监测数据;然后,基于相容矩阵的属性约简算法去除数据冗余属性;最后,基于批量与增量相结合挖掘分类规则,并基于分布计算框架MapReduce应用上述规则实现慢性病变智能分级.实验验证表明,该方法具有较高的识别准确率,有助于个体全面认识健康风险状况.
Abstract:Because of physiological monitoring data has time continuity, inaccuracy, and fuzziness, the traditional classification algorithm is difficult to be used directly. In view of the above problems, a classification method of chronic lesions based on rough sets is proposed. First, the physiological monitoring data are discretized based on fusion of correlation and Chi-merge statistics. Then, this method uses the attribute reduction algorithm based on the compatibility matrix to remove the redundant attributes of the data. Finally, classification rules are mined based on batch and incremental data, and intelligent classification of chronic diseases can be realized by applying the above rules based on MapReduce framework. Experiments show that the method has a high recognition rate, which is helpful for the individual to fully understand the health risks.
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基金项目:国家自然科学基金(61872436);福建省自然科学基金(2018J01570);厦门市高校科技创新项目(3502Z20173035);赛尔网络下一代互联网技术创新项目(NGI20160708)
引用文本:
胡建强,王元.基于粗糙集的慢性病变分级方法.计算机系统应用,2018,27(12):268-273
HU Jian-Qiang,WANG Yuan.Classification Method of Chronic Lesions Based on Rough Sets.COMPUTER SYSTEMS APPLICATIONS,2018,27(12):268-273

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