It is important to understand the different machine learning algorithm. We have already discussed Logistic regression (if you want to know about logistic regression, please
We will discuss K Nearest Neighbours
In the arena of classification algorithm, K Nearest Neighbours or KNN as known popularly is one of the most used algorithm. The algorithm uses classification function to classify objects at the local level deferring all the calculations until complete classification is achieved, hence, this algorithm is also known as the lazy learning algorithm.
The algorithm works by selecting the k nearest neighbours from the training samples based on proximity probability and the distance measure for the test sample and then the algorithm predicts the test sample with the major class amongst k ( as specified by the user) nearest training samples.
If you are interested in how to apply K Nearest Neighbours classification algorithm and the mathematical intuition behind it, you can express your interest in joining the data science boot camp for free by email to
