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 ...

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, ...

Logistic Regression attains an accuracy of 0.969 and a F1-score of 0.628. Classification is a popular task in the field of Machine Learning (ML) and Artificial Intelligence (AI), and it happens ...

Machine learning offers new way of designing chiral crystals Logistic regression analysis model predicts ideal chiral crystal Date: April 10, 2018 Source: Hiroshima University Summary: ...

There has been much recent interest in use of machine learning (ML) for cancer prediction, but few studies comparing ML with classical statistical models for NCGC risk prediction. Methods We trained ...