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Establishment and evaluation of the sub-health diagnosis model based on decision tree

机译:基于决策树的亚健康诊断模型的建立与评估

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The paper introduces the idea of data mining on the basis of analyzing sub-health status quo and existing defects. An influencing-factor-model of sub-health state has been established with the help of the Microsoft decision trees technology, after evaluation, its accuracy rate reaches up to 89.81%. This model serves an important reference for the sub-health diagnosis, prevention and treatment, thus it has a wide range of practical value and significance.
机译:本文介绍了在分析亚健康状态和现有缺陷的基础上介绍了数据挖掘的想法。在评估后,在微软决策树技术的帮助下,已经建立了亚健康状态的影响因素模型,其准确性率达到高达89.81%。该模型为亚健康诊断,预防和治疗提供了重要的参考,因此它具有广泛的实用价值和意义。

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