KNN algorithm

1. What is KNN algorithm?
2. What is KNN algorithm example?
3. Why KNN algorithm is used?
4. Is KNN a simple algorithm?

What is KNN algorithm?

K-Nearest Neighbors Algorithm. The k-nearest neighbors algorithm, also known as KNN or k-NN, is a non-parametric, supervised learning classifier, which uses proximity to make classifications or predictions about the grouping of an individual data point.

What is KNN algorithm example?

With the help of KNN algorithms, we can classify a potential voter into various classes like “Will Vote”, “Will not Vote”, “Will Vote to Party 'Congress', “Will Vote to Party 'BJP'. Other areas in which KNN algorithm can be used are Speech Recognition, Handwriting Detection, Image Recognition and Video Recognition.

Why KNN algorithm is used?

Usage of KNN

The KNN algorithm can compete with the most accurate models because it makes highly accurate predictions. Therefore, you can use the KNN algorithm for applications that require high accuracy but that do not require a human-readable model. The quality of the predictions depends on the distance measure.

Is KNN a simple algorithm?

What is KNN? K Nearest Neighbour is a simple algorithm that stores all the available cases and classifies the new data or case based on a similarity measure. It is mostly used to classifies a data point based on how its neighbours are classified.