The logistic regression model can be represented with the following formula: Where the left side of the equation is the probability the outcome variable Y is 1 given the explanatory variables X. The ...

A new study investigated how logistic regression model training affects performance, and which features are best to include when examining datasets from individuals suffering from COVID-19.

Logistic Regression Model Evaluation: Assessing Performance and Accuracy. Data professionals use various statistical methods to assess the performance and accuracy of logistic regression models.

When training a logistic regression model, there are many optimization algorithms that can be used, such as stochastic gradient descent (SGD), iterated Newton-Raphson, Nelder-Mead and L-BFGS. This ...

Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

There are many different algorithms that can be used to train a multi-class logistic regression model and each algorithm has several variations. Common algorithms include stochastic gradient descent ...

A diagnostic model based on delayed post-gadolinium enhancement magnetic resonance imaging (DEMRI) improves the accuracy of ...

Logistic Regression Model to Distinguish Between the Benign and Malignant Adnexal Mass Before Surgery: A Multicenter Study by the International Ovarian Tumor Analysis Group . JCO 23 , 8794-8801 (2005) ...