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

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 ...

This is closely related to the traditional statistical application of the method, the key difference being that in machine learning, logistic regression is used to develop a model that learns from ...

Early prediction of in-hospital pneumonia mortality can effectively be done using a machine learning (ML) model based on clinical data.

Machine learning prediction model analytic pipeline ... receiver operating characteristics of prediction models in the Stanford testing set: logistic regression (blue, AUC, 0.779), penalized lasso ...