Comparison between Statistical Models and Machine Learning Methods on Classification for Highly Imbalanced Multiclass Kidney Data

Comparison between Statistical Models and Machine Learning Methods on Classification for Highly Imbalanced Multiclass Kidney Data

This study aims to compare the classification performance of statistical models on highly imbalanced kidney data. The health examination cohort database provided by the National Health Insurance Service in Korea is utilized to build models with various machine learning methods. The glomerular filtra...

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Bibliographic Details
Main Authors: Bomi Jeong, Hyunjeong Cho, Jieun Kim, Soon Kil Kwon, SeungWoo Hong, ChangSik Lee, TaeYeon Kim, Man Sik Park, Seoksu Hong, Tae-Young Heo
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Diagnostics
Subjects:
imbalanced data
autoencoder
machine learning
chronic kidney disease
national health screening
Online Access:https://www.mdpi.com/2075-4418/10/6/415

Internet

https://www.mdpi.com/2075-4418/10/6/415

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