AdaBoost算法在慢性肾脏疾病预测中的实现

T. Asra, Ahmad Setiadi, Mahmud Safudin, Endah Wiji Lestari, Nila Hardi, D. Alamsyah
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引用次数: 6

摘要

肾脏是人体重要器官之一,担负着维持人体健康的各种任务。其中之一是去除血液中多余的水分和毒素。慢性肾脏病是一种进行性和不可逆的干扰肾功能的疾病,在这种疾病中,身体的能力无法维持新陈代谢和液体和电解质的平衡,导致尿毒症。有许多研究旨在预测慢性肾脏疾病。本研究采用C4.5算法作为分类算法,并加入Adaboost算法。结果表明,使用该算法获得的精度值为95%,精度为92%,曲线下面积为1。而结合Adaboost算法得到的精度值为precision,和Area Under the Curve by 1。从结果的准确度、精度和Area Under the Curve可以看出,在算法中使用Adaboost可以很好的提高准确度和精度的结果,因为Area Under the Curve的值是可以接受的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of AdaBoost Algorithm in Prediction of Chronic Kidney Disease
The kidneys are one of the important organs for humans with various tasks to keep humans healthy. One of them is to remove excess water and toxins from the blood. The chronic kidney is a disease that interferes with kidney function that is progressive and irreversible in which the body’s ability to fail to maintain metabolism and fluid and electrolyte balance resulting in uremia. There have been many studies aimed at predicting chronic kidney disease. In this study, using the C4.5 algorithm as a classification algorithm and by adding the Adaboost algorithm. The results showed that using the algorithm obtained an accuracy value of 95%, 92% precision, and Area Under the Curve by 1. Whereas using the algorithm combined with Adaboost got an accuracy value is precision, and Area Under the Curve by 1. Based on the results accuracy, precision, and Area Under the Curve, it can be seen by using Adaboost in the algorithm can improve the results of accuracy and precision with very good classification, because the Area Under the Curve value is accepted.
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