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K-nearest neighbors algorithm

Known as: Ibk algorithm, Nearest neighbors classifier, K-NN 
In pattern recognition, the k-Nearest Neighbors algorithm (or k-NN for short) is a non-parametric method used for classification and regression. In… 
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Related topics

Related topics

47 relations
Anomaly detectionArrayTrackBelur V. DasarathyBias–variance tradeoff

Broader (1)

Statistical classification

Papers overview

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Highly Cited
2015
Highly Cited
2015
An Empirical Study of Distance Metrics for k-Nearest Neighbor Algorithm
This research aims at studying the performance of k-nearest neighbor classification when applying different distance measurements… 
Highly Cited
2014
Highly Cited
2014
Diagnosis of Diabetes Mellitus using K Nearest Neighbor Algorithm
Diabetes is one of the major global health problems. According to WHO 2011 report, around 346 million people worldwide are… 
Highly Cited
2014
Highly Cited
2014
Anomaly Detection Using Self-Organizing Maps-Based K-Nearest Neighbor Algorithm
Self-organizing maps have been used extensively for condition-based maintenance, where quantization errors of test data referring… 
Highly Cited
2012
Highly Cited
2012
Enhanced weighted K-nearest neighbor algorithm for indoor Wi-Fi positioning systems
Location-based systems for indoor positioning have been studied widely owing to their application in various fields. The… 
Highly Cited
2010
Highly Cited
2010
An adaptive k-nearest neighbor algorithm
An adaptive k-nearest neighbor algorithm (AdaNN) is brought forward in this paper to overcome the limitation of the traditional k… 
Highly Cited
2009
Highly Cited
2009
How k-nearest neighbor parameters affect its performance
The k-Nearest Neighbor is one of the simplest Machine Learning algorithms. Besides its simplicity, k-Nearest Neighbor is a widely… 
Highly Cited
2005
Highly Cited
2005
Monitoring k-nearest neighbor queries over moving objects
Many location-based applications require constant monitoring of k-nearest neighbor (k-NN) queries over moving objects within a… 
Highly Cited
2004
Highly Cited
2004
An Investigation of Practical Approximate Nearest Neighbor Algorithms
This paper concerns approximate nearest neighbor searching algorithms, which have become increasingly important, especially in… 
Highly Cited
2001
Highly Cited
2001
Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification
Text categorization presents unique challenges due to the large number of attributes present in the data set, large number of… 
Highly Cited
2001
Highly Cited
2001
K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms
Guided by an initial idea of building a complex (non linear) decision surface with maximal local margin in input space, we give a… 
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