A non-linear SVR-based cascade model for improving prediction accuracy of biomedical data analysis

A non-linear SVR-based cascade model for improving prediction accuracy of biomedical data analysis

Biomedical data analysis is essential in current diagnosis, treatment, and patient condition monitoring. The large volumes of data that characterize this area require simple but accurate and fast methods of intellectual analysis to improve the level of medical services. Existing machine learning (ML...

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Bibliographic Details
Main Authors: Ivan Izonin, Roman Tkachenko, Olexander Gurbych, Michal Kovac, Leszek Rutkowski, Rostyslav Holoven
Format: Article
Language:English
Published: AIMS Press 2023-06-01
Series:Mathematical Biosciences and Engineering
Subjects:
cascading
data analysis
biomedical data
ito decomposition
ensemble model
linear support vector machine
non-linear input extension
prediction tasks
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2023597?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/mbe.2023597?viewType=HTML

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