Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Heart failure with reduced ejection fraction (HFrEF) represents a significant global health burden, affecting over 64 million individuals and resulting in substantial morbidity and mortality, ...

A UK study found that nearly all families occasionally eat takeaway food together, with most using it as a convenient, social ...

The following is a summary of “A risk nomogram for assessing complications in patients undergoing surgical procedures for ...

One year of weather data (temperature, pressure, humidity, sunshine, evaporation, cloud cover, wind direction, and wind speed) from Canberra, Australia, has been used to develop the logistic ...

we extended the binary logistic regression models by allowing random effects to accommodate correlations. The hierarchical nature of the DHS data, which violates the independence assumptions of the ...

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