基于CatBoost算法的糖尿病预测方法  

Diabetes Prediction Method Based on CatBoost Algorithm

作　　者：苗丰顺 李岩[2] 高岑[2] 王美吉[2] 李冬梅 MIAO Feng-Shun;LI Yan;GAO Cen;WANG Mei-Ji;Li Dong-Mei(University of Chinese Academy of Sciences,Beijing 100049,China;Shenyang Institute of Computing Technology,Chinese Academy of Sciences,Shenyang 110168,China)

机构地区：[1]中国科学院大学,北京100049 [2]中国科学院沈阳计算技术研究所,沈阳110168

出　　处：《计算机系统应用》2019年第9期215-218,共4页Computer Systems & Applications

摘　　要：近几十年来,人们生活水平显著提高,但是健康意识依旧薄弱,不良的生活习惯和饮食习惯导致糖尿病发病人数急剧增加,由糖尿病导致的各种并发症严重威胁了人们的健康.由于糖尿病具有知晓率低的特点,很多糖尿病患者未能及时发现病症,导致出现并发症.本文通过分析糖尿病的特点,针对医疗数据样本量小、容易缺失的特点,选择Ⅳ值分析进行特征选择、使用一种新型的Boosting算法CatBoost进行糖尿病患者预测,取得了显著的预测效果.In recent decades, people’s living standards have improved significantly, but health awareness is still weak.Poor living habits and eating habits have led to a sharp increase in the number of people with diabetes. The complications caused by diabetes are a serious threat to people’s health. Because awareness rate of diabetes is low, many patients with diabetes fail to detect the disease in time, leading to complications. In this study, by analyzing the characteristics of diabetes, according to the characteristics of small sample size and easy to be missing, the Ⅳ value analysis is used for feature selection, and CatBoost, a new type of Boosting algorithm, is used to predict diabetes patients and achieves significant predictive effects.

关 键 词：糖尿病 Ⅳ值分析 特征选择 集成学习 CatBoost 

分 类 号：R58[医药卫生—内分泌]