Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Dr. James McCaffrey of Microsoft Research says the main advantage of scikit is that it's easy to use (even though most classes have many constructor parameters). Logistic regression is a machine ...

Vol. 27, No. 3, Contributions to the 7th Conference on Multivariate Distributions with Applications and 1st Conference on Applied Probability and Statistical Methods (August 2013), pp. 265-284 (20 ...

A class of conditional logistic regression models for clustered binary data is considered. This includes the polychotomous logistic model of Rosner (1984) as a special case. Properties such as the ...

Increased triglyceride-glucose (TyG) index values are strongly associated with decreased lung function in healthy individuals.