Logistic regression is a technique used to make predictions in situations where the item to predict can take one of just two possible values. For example, you might want to predict the credit ...

Learn how to detect and handle perfect separation in logistic regression models, using different methods and tools. Find out how to choose the best method for your data and research question.

The random forest model significantly outperformed all other models, including the logistic regression model that the entire paper focuses on, with an eventual AUC of 0.936 and an accuracy of 0.918.

Methods are developed for fitting logistic models to data in which cases and/or controls are sampled from the available cases and controls within population strata. Particular attention is paid to ...

Tadikamalla and Johnson [Biometrika 69 (1982) 461–465] developed the LB distribution to variables with bounded support by considering a transformation of the standard Logistic distribution. In this ...

First off, you need to be clear what exactly you mean by advantages. People have argued the relative benefits of trees vs. logistic regression in the context of interpretability, robustness, etc.

Employee Well-being is the physical and psychological experience and feeling of employees during work, it is a critical indicator of employee's quality of life and plays an important role in ...

This study proposes a comprehensive approach that combines Chi-squared and XGBoost feature selection methods with logistic regression and Decision Tree classification models. By leveraging these ...