Logistic regression is preferrable over a simpler statistical test such as chi-squared test or Fisher’s exact test as it can incorporate more than one explanatory variable and deals with possible ...

Accuracy, Precision, and F1 Score. Data practitioners can use the numbers derived from a confusion matrix to calculate their logistic regression models’ accuracy, recall, and F1 score.

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 ...

Understanding How Logistic Regression Works Understanding how logistic regression works is best explained by example. Suppose, ... but the most common, and the default, is 'lbgs' (limited-memory ...

Materials and methods: We compared traditional logistic regression (LR) with five ML algorithms LR with Elastic-Net, Random Forest (RF), XGBoost (XGB), Support Vector Machine, Deep Learning, and an ...

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, ...