Nearest neighbor pattern classification

1967/01/01 by T. Cover, Thomas M. Cover, P. Hart +1 · 16,401 citations
Computer Science · Mathematics · #Advanced Statistical Methods and Models #Algorithm #Artificial intelligence #Bayes' theorem #Bayesian probability #Combinatorics #Computer science #Mathematics #Pattern recognition (psychology) #Probability distribution #Rough Sets and Fuzzy Logic #Statistical Methods and Inference #Statistics #k-nearest neighbors algorithm

paper · doi:10.1109/tit.1967.1053964

published in IEEE Transactions on Information Theory 13(1), 21-27 (Institute of Electrical and Electronics Engineers)

openalex publication_date 1967/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points. This rule is independent of the underlying joint distribution on the sample points and their classifications, and hence the probability of errorRof such a rule must be at least as great as the Bayes probability of errorR^∗--the minimum probability of error over all decision rules taking underlying probability structure into account. However, in a large sample analysis, we will show in theM-category case thatR^∗ ≤ R ≤ R^∗(2 --MR^∗/(M-1)), where these bounds are the tightest possible, for all suitably smooth underlying distributions. Thus for any number of categories, the probability of error of the nearest neighbor rule is bounded above by twice the Bayes probability of error. In this sense, it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.

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• Video-Based Facial Expression Recognition Using Local Directional Binary Pattern
• A Latent Source Model for Nonparametric Time Series Classification
• Machine learning embedded hybrid MCDM model to mitigate decision uncertainty in transport safety planning for OAS countries
• On k-Nearest Neighbor Voronoi Diagrams in the Plane
• Impact of Iridium Crucible Aging on Cz‐YAG Crystal Quality and Process Economy: A Data‐Driven Study
• Element-Grouping Strategy for Intelligent Reflecting Surface: Performance Analysis and Algorithm Optimization
• Boosting KNNClassifier Performance with Opposition-Based Data Transformation
• RadioDiff-k²: Helmholtz Equation Informed Generative Diffusion Model for Multi-Path Aware Radio Map Construction
• Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study
• Semantic Search of Memes on Twitter
• PLIERS at TREC8 - Appendix
• Dual Space Graph Contrastive Learning
• RadioDiff-Inverse: Diffusion Enhanced Bayesian Inverse Estimation for ISAC Radio Map Construction
• An Efficient Approach to Learning Chinese Judgment Document Similarity Based on Knowledge Summarization
• Automated design of heuristics for resource-constrained project scheduling problem via regression algorithms
• The Efficacy of Various Machine Learning Models for Multi-class Classification of RNA-Seq Expression Data
• Development of Machine Learning in Organic Photovoltaic Cells †
• Semantic Segmentation of Remote Sensing Images With Sparse Annotations
• Supervised Metric Learning with Generalization Guarantees
• Graph-Regularized Point-to-Trajectory Association for RS-AIS fusion toward maritime moving-ship identification and spatial refinement
• Enhancing induction machine fault detection through machine learning: Time and frequency analysis of vibration signals
• GEOMETRIC PROXIMITY GRAPHS FOR IMPROVING NEAREST NEIGHBOR METHODS IN INSTANCE-BASED LEARNING AND DATA MINING
• Machine Learning Reveals Composition Dependent Thermal Stability in Halide Perovskites
• Q-Cluster: Quantum Error Mitigation Through Noise-Aware Unsupervised Learning
• Correcting Domain Shifts in Electric Motor Vibration Data for Unseen Operating Conditions
• CKMImageNet: A Dataset for AI-Based Channel Knowledge Map Towards Environment-Aware Communication and Sensing
• A survey on recent trends in robotics and artificial intelligence in the furniture industry
• MMLTC : A Novel Tolerance‐Based Clustering Framework for Multimodal Sentiment and Harmful Meme Classification in Multilingual Settings
• A review of “perceptrons: An introduction to computational geometry≓
• Classification of schizophrenia patients based on resting-state functional network connectivity. [europepmc]
• The distance function effect on k-nearest neighbor classification for medical datasets. [europepmc]
• A real-time phenotyping framework using machine learning for plant stress severity rating in soybean. [europepmc]
• Individual Differences in Frequency and Topography of Slow and Fast Sleep Spindles. [europepmc]
• In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts. [europepmc]
• A Review of Emotion Recognition Using Physiological Signals. [europepmc]
• Machine Learning Based Toxicity Prediction: From Chemical Structural Description to Transcriptome Analysis. [europepmc]
• A Comprehensive Review of Magnetoencephalography (MEG) Studies for Brain Functionality in Healthy Aging and Alzheimer's Disease (AD). [europepmc]
• Predicting patient-reported outcomes following hip and knee replacement surgery using supervised machine learning. [europepmc]
• Comparing different supervised machine learning algorithms for disease prediction. [europepmc]
• Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone. [europepmc]
• CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity. [europepmc]
• An artificial intelligence decision support system for the management of type 1 diabetes. [europepmc]
• Machine learning-guided discovery and design of non-hemolytic peptides. [europepmc]
• Embeddings from deep learning transfer GO annotations beyond homology. [europepmc]
• CATMoS: Collaborative Acute Toxicity Modeling Suite. [europepmc]
• α-Synuclein in blood exosomes immunoprecipitated using neuronal and oligodendroglial markers distinguishes Parkinson's disease from multiple system atrophy. [europepmc]
• Identification of microbial markers across populations in early detection of colorectal cancer. [europepmc]
• A deep look into radiomics. [europepmc]
• Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application. [europepmc]
• Single-nucleus RNA-sequencing of autosomal dominant Alzheimer disease and risk variant carriers. [europepmc]
• Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review. [europepmc]
• A Review of Single-Cell RNA-Seq Annotation, Integration, and Cell-Cell Communication. [europepmc]
• Accurately identifying hemagglutinin using sequence information and machine learning methods. [europepmc]
• Self-Driving Laboratories for Chemistry and Materials Science. [europepmc]

Related

• Asymptotic Properties of Nearest Neighbor Rules Using Edited Data
• Classification with the nearest neighbor rule in general finite dimensional spaces: necessary and sufficient conditions
• Local nearest neighbour classification with applications to semi-supervised learning
• Nearest Neighbor Classification based on Imbalanced Data: A Statistical Approach
• Speculate-Correct Error Bounds for k-Nearest Neighbor Classifiers