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 Applications Most logistic regression use cases involve binary logistic regression, determining whether an example belongs to a particular class.

This article derives a new family of estimators, namely the minimum density power divergence estimators, as a robust generalization of the maximum likelihood estimator for the polytomous logistic ...

Jason A. Schoeneberger, The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models, The Journal of Experimental Education, Vol. 84, No. 2 (2016), pp. 373-397 ...

Next, the demo creates and trains a logistic regression model using the LogisticRegression class from the scikit library. [Click on image for larger view.] Figure 1: Logistic Regression Using scikit ...

Disease duration, disease activity, osteoporosis, and CRP levels were identified as predictors of MCI among older patients with RA.

A large study of a school-based eye exam program found substantial need for new and updated eyeglass prescriptions, particularly in boys and those in higher grade levels, according to an analysis ...