A Review of Data Classification Using K-Nearest Neighbour Algorithm
Aman Kataria, Moninder Singh · 2013
Abstract—To classify data whether it is in the field of neural networks or maybe it is any application of Biometrics viz: Handwriting classification or Iris detection, feasibly the most candid classifier in the stockpile or machine learning techniques is the Nearest Neighbor Classifier in which classification is achieved by identifying the nearest neighbors to a query example and using those neighbors to determine the class of the query. K-NN classification classifies instances based on their similarity to instances in the training data. This paper presents various output with various distance used in algorithm and may help to know the response of classifier for the desired application it also represents computational issues in identifying nearest neighbors and mechanisms for reducing the dimension of the data.