Logistic regression

Let's start again with the triple W for logistics regression. To reiterate the tripe W method, we first ask the algorithm what it is, followed by where it can be used, and finally by what method we can implement the model.

What is logistic regression?

Logistic regression can be thought of as an extension to linear regression algorithms. It fundamentally works like linear regression, but it is meant for discrete or categorical outcomes.

Where is logistic regression used?

Logistic regression is applied in the case of discrete target variables such as binary responses. In such scenarios, some of the assumptions of linear regression, such as target attribute and features, don't follow a linear relationship, the residuals might not be normally distributed, or the error terms are heteroscedastic. In logistic regression, the target is reconstructed to the log of its odds ratio to fit the regression equation, as shown here:

The odds ratio reflects the probability or likelihood of...