About this document
K-Nearest Neighbors Algorithm Explained by Avinash S is a document available to read on EtoBox.
The K-Nearest Neighbours (K-NN) algorithm is a simple, lazy learning method used for classification and regression, where it assigns a new data point to the class of its nearest neighbors based on distance measures like Euclidean, Manhattan, and Hamming distances. The choice of K is crucial, as a small K may lead to instability while a large K increases computational complexity. The document also provides examples of K-NN applications in dog breed classification and salary prediction based on age and skill
- Author
- Avinash S
- Language
- EN