The amount of data for decision making has increased tremendously in the age of the digital economy. Decision makers who fail to proficiently manipulate the data produced may make incorrect decisions and therefore har...The amount of data for decision making has increased tremendously in the age of the digital economy. Decision makers who fail to proficiently manipulate the data produced may make incorrect decisions and therefore harm their business. Thus, the task of extracting and classifying the useful information efficiently and effectively from huge amounts of computational data is of special importance. In this paper, we consider that the attributes of data could be both crisp and fuzzy. By examining the suitable partial data, segments with different classes are formed, then a multithreaded computation is performed to generate crisp rules (if possible), and finally, the fuzzy partition technique is employed to deal with the fuzzy attributes for classification. The rules generated in classifying the overall data can be used to gain more knowledge from the data collected.展开更多
为完成乳腺癌诊断规则的可视化提取工作,提出一种基于偏序结构图和套索(lasso)融合原理的乳腺癌计算机辅助诊断方法。以美国威斯康星州医学院WBCD(Wisconsin breast cancer database)为数据样本,利用lasso完成特征提取和属性约简,利用...为完成乳腺癌诊断规则的可视化提取工作,提出一种基于偏序结构图和套索(lasso)融合原理的乳腺癌计算机辅助诊断方法。以美国威斯康星州医学院WBCD(Wisconsin breast cancer database)为数据样本,利用lasso完成特征提取和属性约简,利用数学偏序原理和偏序结构图完成乳腺癌诊断规则的提取。实验结果表明,偏序结构图与lasso相融合的方法可以完成特征约简,有效完成乳腺癌的计算机辅助诊断和规则可视化提取任务,具有较高的诊断准确率,偏序结构图具有很好的知识可视化特性。展开更多
文摘The amount of data for decision making has increased tremendously in the age of the digital economy. Decision makers who fail to proficiently manipulate the data produced may make incorrect decisions and therefore harm their business. Thus, the task of extracting and classifying the useful information efficiently and effectively from huge amounts of computational data is of special importance. In this paper, we consider that the attributes of data could be both crisp and fuzzy. By examining the suitable partial data, segments with different classes are formed, then a multithreaded computation is performed to generate crisp rules (if possible), and finally, the fuzzy partition technique is employed to deal with the fuzzy attributes for classification. The rules generated in classifying the overall data can be used to gain more knowledge from the data collected.
文摘为完成乳腺癌诊断规则的可视化提取工作,提出一种基于偏序结构图和套索(lasso)融合原理的乳腺癌计算机辅助诊断方法。以美国威斯康星州医学院WBCD(Wisconsin breast cancer database)为数据样本,利用lasso完成特征提取和属性约简,利用数学偏序原理和偏序结构图完成乳腺癌诊断规则的提取。实验结果表明,偏序结构图与lasso相融合的方法可以完成特征约简,有效完成乳腺癌的计算机辅助诊断和规则可视化提取任务,具有较高的诊断准确率,偏序结构图具有很好的知识可视化特性。
