If the signal to noise ratio is low (it is a ‘hard’ problem) logistic regression is likely to perform best. In technical terms, if the AUC of the best model is below 0.8, logistic very clearly ...

Logistic regression can be applied in customer service, when you examine historical data on purchasing behaviour to personalise offerings. The afterword We’ve touched upon three common models of ...

Citation: Regression approach outperforms ML algorithms in predicting optimal surgical method in submucosal tumor patients (2024, February 28) retrieved 15 May 2025 from https://medicalxpress.com ...

A Comparison of Logistic Regression Against Machine Learning Algorithms for Gastric Cancer Risk Prediction Within Real-World Clinical Data Streams. JCO Clin Cancer Inform 6 , e2200039 (2022). DOI: ...

EHR data may be particularly suitable for machine learning (ML) techniques, as such algorithms can process high-dimensional data and capture nonlinear relationships between variables. By comparison, ...