K- Nearest Neighbor Algorithm for Instance Based Learning

Abstract

Instance Based Learning (IBL) results in classifying a new instance by examining and comparing it to the rest of the instances in the dataset. An example of this type of learning is the K-Nearest Neighbor algorithm which is based on examining an average Euclidian distance of the nearest k neighbors' parameters given a certain situation.

Cite this paper

@inproceedings{Stanciu2013KNN, title={K- Nearest Neighbor Algorithm for Instance Based Learning}, author={Cristina Ofelia Stanciu}, year={2013} }