Simple Logistic Regression in Python

Step-by-Step Guide from Data Preprocessing to Model Evaluation

logistic regression python cheatsheet (image by author from www.visual-design.net)

What is Logistic Regression?

Don’t let the name logistic regression tricks you, it usually falls under the category of the classification algorithm instead of regression algorithm.

Then, what is a classification model? Simply put, the prediction generated by a classification model would be a categorical value, e.g. cat or dog, yes or no, true or false … On the contrary, a regression model would predict a continuous numeric value.

Logistic regression makes predictions based on the Sigmoid function which is a squiggles-like line as shown below. Despite the fact that it returns the probabilities, the final output would be a label assigned by comparing the probability with a threshold, which makes it eventually a classification algorithm.

simple illustration of sigmoid function (image by author)

In this article, I will walk through the following steps to build a simple logistic regression model using python scikit -learn:

1. Data Preprocessing
2. Feature Engineering and EDA