The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity. The goal of a ...

In this article, we provide a random utility-based derivation of the Dirichlet-multinomial regression and propose it as a convenient alternative for dealing with overdispersed multinomial data. We ...

The fundamental technique has been studied for decades, thus creating a huge amount of information and alternate variations that make it hard to tell what is key vs. non-essential information.

There is no established procedure for testing for trend with nominal outcomes that would provide both a global hypothesis test and outcome-specific inference. We derive a simple formula for such a ...

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 ...

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you understand ...