按车对肝硬化疾病进行分类

Yasmin Roni Mz, Komang Gde Sukarsa, Gusti Ayu, Made Srinadi
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引用次数: 0

摘要

非参数探索法是一种可以用来观察因变量和自变量之间关系的方法。CART 就是其中一种非参数探索性方法。CART 是一种将大量数据以决策树的形式呈现出来并进行处理的方法,从而使其成为有价值且易于理解的信息。本研究旨在利用 CART 建立一个基于肝硬化患者医疗记录的决策树模型。本研究还使用了 276 个数据中的 16 个自变量作为研究对象。研究结果得到了一个带有自变量的决策树模型。第一个用作根节点的是肝肿大,因为与其他自变量相比,肝肿大变量的值更具有同质性,而且本研究中共有八个组。然而,由于 CART 方法的不稳定性和对新数据的敏感性,以及对样本数量的高度依赖性,本研究的准确率低于 70%,这是因为一组数据与另一组数据相比是不平衡的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
KLASIFIKASI PENYAKIT SIROSIS HATI DENGAN CART
The nonparametric exploratory is a method that can be used to see the relationship between the dependent variable and the independent variable. One of the types of nonparametric exploratory methods is the CART. CART is a method that presents large amounts of data to be processed in the form of a decision tree so that it becomes valuable and easy to understand information. This research aims to build a decision tree model based on medical records from patients with liver cirrhosis using the CART. This research also used 16 independent variables of 276 data that will be used as research objects. The results of this study obtained a decision tree model with an independent variable. The first used as the root node is hepatomegaly because the hepatomegaly variable has a more homogeneous value compared to the other independent variables and that there were eight groups in this research. However, due to the nature of the CART method which is unstable and very sensitive to new data, and highly dependent on the number of samples, the accuracy rate in this study is less than 70%, this is because the data in one group is unbalanced if compared to data in the other group.
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