The nested logistic regression models were then retrained on the new dataset, with retraining performed using the train split of the expanded dataset and performance evaluated using the test split ...

Understanding Logistic Regression Logistic regression is best explained by example. Suppose that instead of the Patient dataset you have a simpler dataset where the goal is to predict gender from x0 = ...

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.

Kin-Yee Chan, Wei-Yin Loh, LOTUS: An Algorithm for Building Accurate and Comprehensible Logistic Regression Trees, Journal of Computational and Graphical Statistics, Vol. 13, No. 4 (Dec., 2004), pp.

A shared parameter model with logistic link is presented for longitudinal binary response data to accommodate informative drop-out. The model consists of observed longitudinal and missing response ...