While multiple machine learning (ML) algorithms offered similar predictive performance, the cost-effective analysis revealed ...

As the coronavirus disease 2019 (COVID-19) pandemic has spread across the world, vast amounts of bioinformatics data have been created and analyzed, and logistic regression models have been key to ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable ...

More information: Haoyang Hong et al, simpleNomo: A Python Package of Making Nomograms for Visualizable Calculation of Logistic Regression Models, Health Data Science (2023). DOI: 10.34133/hds.0023 ...

The overall program structure is presented in Listing 1 ... can often produce better prediction models, logistic regression is still considered one of the main workhorses of machine learning. In ...

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...

The least absolute shrinkage and selection operator-logistic regression (Lasso-LR) model is optimal for predicting ...