Isotonic regression

Isotonic regression is a type of machine learning (ML) technique that helps us find the best possible fit between two kinds of data. Imagine you have a list of temperatures and you want to find the 'best' line to fit them. Isotonic regression uses an algorithm to find that line which gives the most accurate fit. It starts by looking at the first two points in our list of temperatures and finds the best fit between them. Then it moves on to the next two points and finds the best fit for them. It continues this process until it has looked at all the points and found the best fit for all of them. In this way, isotonic regression helps us find the best possible fit between two sets of data.