Batch Gradient Ascent and Logistic Regression

Photo by Giuseppe Famiani on Unsplash

For this blog, I will explain logistic regression and how the beta values can be calculated through gradient ascent of the maximum log-likelihood.

Logistic regression is widely used for binary classifications where the dependant variables are limited to be either 0 or 1. Therefore, our predicted values should also range between 0 and 1 with a 50% threshold. This is to say, if the model…