A Review on K nearest Neighbour Classification Technique in Machine Learning

Dr. G. Vijaya Lakshmi

doi:10.32628/IJSRSET25121168

Authors

Dr. G. Vijaya Lakshmi Assistant Professor, Department of Computer Science, Vikrama Simhapuri University, Kakutur, Nellore, - 524320, Andhra Pradesh, India Author

DOI:

https://doi.org/10.32628/IJSRSET25121168

Keywords:

Dissimilarity measures, Euclidian distance, Rank, lazy learners, KNN

Abstract

Classification is a Supervised Learning technique which is used to predict the correct category from the given input features. Logistic regression, decision trees, random forests, support vector machines (SVM), naive bayes, and K-nearest neighbors (KNN) are some of the several classification techniques.. This paper discusses the KNN classification technique, which uses the similarity measure of previously stored data points to classify new data points.

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