There are many other techniques for binary classification, but logistic regression was one of the earliest developed and the technique is considered a fundamental machine learning skill for data ...

In the production of 1990 undercount estimates, the basic logistic regression model was expanded into a mixed hierarchical model to allow for the presence of group-specific effects, where groups are ...

Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to ...

Many machine learning code libraries have built-in multi-class logistic regression functionality. However, coding multi-class logistic regression from scratch has least four advantages over using a ...

Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies.