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k-Nearest Neighbors
conceptMachine Learning Algorithm
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Overview
Developed byEvelyn Fix and Joseph Hodges
Open source✓ Open Source
Use caseclassification and regression tasks in machine learning
Knowledge graph stats
Claims18
Avg confidence92%
Avg freshness99%
Last updatedUpdated 5 days ago
WikidataQ628048
Trust distribution
100% unverified
Governance
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k-Nearest Neighbors

concept

Algorithm for finding the k closest data points to a query point in vector space for classification or search.

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implemented in

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scikit-learn○UnverifiedHighFresh1
Weka○UnverifiedModerateFresh1

implemented by

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scikit-learn○UnverifiedHighFresh1
Weka○UnverifiedHighFresh1

supports distance metric

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Euclidean distance○UnverifiedHighFresh1
Manhattan distance○UnverifiedHighFresh1

open source

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true○UnverifiedHighFresh1

primary use case

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classification and regression tasks in machine learning○UnverifiedHighFresh1
classification○UnverifiedHighFresh1
recommendation systems○UnverifiedModerateFresh1

algorithm type

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non-parametric supervised learning algorithm○UnverifiedHighFresh1

based on

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instance-based learning principle○UnverifiedHighFresh1

also known as

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lazy learning algorithm○UnverifiedHighFresh1

requires

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distance metric for similarity calculation○UnverifiedHighFresh1

developed by

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Evelyn Fix and Joseph Hodges○UnverifiedHighFresh1

computational complexity

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O(n) for prediction where n is training set size○UnverifiedHighFresh1

use case

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recommendation systems○UnverifiedModerateFresh1

alternative to

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decision trees○UnverifiedModerateFresh1

Alternatives & Similar Tools

decision trees
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Claim count: 18Last updated: 4/5/2026Edit history