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Improved Ensemble Classification Method for Thyroid Disease Using Data Mining Technologies

机译:利用数据挖掘技术改进了甲状腺疾病的集合分类方法

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Data mining plays an important role in various healthcare services. The most complicated task is to identify the disease and diagnosing it at a prompt phase. One of the most important functions of the health-care providers is to diagnose illness and save lives. The main aim of any healthcare domain is to discover and diagnose the disease at premature stages with higher accuracy. For providing the treatment in low cost, data mining is considered as the best technique. In healthcare industry, the usage of automated diagnostic systems has become more common in recent years. These systems offer several advantages in the diagnosis process. This paper will explain the aspects of Feature Engineering to solve the problem of dealing with large data sets. Also, the proposed research work has used the concept of feature engineering to solve the issue of large data sets with the algorithm of Instance Selection that combines the two algorithms of Instance Selection using drop1 algorithm and Instance Selection algorithm using Boosting.
机译:数据挖掘在各种医疗保健服务中起着重要作用。最复杂的任务是识别疾病并在提示阶段诊断。医疗保健提供者最重要的功能之一是诊断疾病并拯救生命。任何医疗领域的主要目的是以更高的准确度在早产的阶段发现和诊断疾病。为了以低成本提供处理,数据挖掘被认为是最好的技术。在医疗保健行业中,近年来,自动化诊断系统的使用变得更加普遍。这些系统在诊断过程中提供了几个优点。本文将解释要解决处理大数据集的问题的特征工程的方面。此外,拟议的研究工作已经利用了特征工程的概念来解决与实例选择算法的大数据集问题,该算法使用DAMP1算法和使用升压的实例选择算法来组合两种实例选择算法。

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