Evolutionary Machine Learning for Intelligent Health Risk Prediction

Abstract excerpt

Evolutionary Machine Learning (EML) has demonstrated its effectiveness in modeling various real-world application domains, including the dynamics of diseases and the creation of predictive models across diverse fields. However, the challenge of data imbalance adversely impacts the performance of EML models. While strategies involving misclassification costs or cost-sensitive learning exist to address this issue, t...

Topics

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• Algorithms
• Area Under Curve
• Decision Support Systems, Clinical
• Machine Learning
• Reproducibility of Results
• Software
• Stochastic Processes
• Support Vector Machine

Identifiers and source

Literature Corpus work

ab6ec430-1f9c-5cc1-b567-9835638a0e3b

DOI

10.20944/preprints202401.0753.v1