What is KNN algorithm in Machine Learning

It appears in a lot of Machine Learning interviews that, What is the KNN algorithm in Machine Learning? Today we are going to discuss it in depth. Read the full post to get a basic understanding of the KNN algorithm.

Suppose we have a test Input X and we have to classify this X into a label based on our training dataset. How can we do this? Through the KNN algorithm we have to classify X based on its K neighbours. Let’s say we are classifying X based on K=3, so in order to label the X, we will look into the 3 nearest neighbours of X, so if among the 3 neighbours if 2 labels are Yes then, we will classify X as Yes. See the image below.

What is KNN algorithm in Machine Learning

Formal Definition of KNN algorithm in Machine Learning

Assuming x to be our test point, let’s denote the set of the k nearest neighbours of x as S. Formally, S is defined as

  • S subset of D(all data points)
  • |S| = K
  • Every Point that is in D but not in S is at least as far away from x as the furthest point in S
  • Where h() is classifier which returns the most common label available in S

The Wikipedia Definition of the KNN algorithm is HERE.

What if Set S contain equal numbers of labels. For example, it contains two Yes and two No?

We usually take K as an odd number so that there will be more Yes labels or more No labels.


Data Science related posts visit HERE

Algorithms related posts visit HERE

Data Structures related posts visit HERE

Databases related posts Visit HERE

Python-related posts Visit HERE

C++ related posts Visit HERE

Share the Knowledge