We propose consistent functional methods for logistic regression in which some covariates are not accurately ascertainable. Among existing methods for generalized linear models, the conditional-score ...

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 demonstrates applying the L-BFGS optimization algorithm to the ML logistic regression technique for binary classification -- predicting one of two possible ...

Dr. James McCaffrey of Microsoft Research uses a full code program, examples and graphics to explain multi-class logistic regression, an extension technique that allows you to predict a class that can ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

In epidemiological studies, continuous covariates often are measured with error and categorical covariates often are misclassified. Using the logistic regression ...

Introduction Caesarean section rates have increased globally, exceeding the WHO’s recommended threshold of 15%. Understanding ...