kNear
JavaScript implementation of the k nearest neighbors algorithm for supervised learning.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is kNear?
kNear is a JavaScript library that provides an easy-to-use implementation of the k-nearest neighbors algorithm, enabling developers to perform supervised machine learning tasks directly in their web applications or Node.js projects.
Key differentiator
“kNear stands out as a lightweight, pure JavaScript implementation of the k-nearest neighbors algorithm, making it ideal for developers looking to integrate machine learning directly into their web or Node.js projects without external dependencies.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
kNear primarily focuses on k-nearest neighbors and lacks support for more complex algorithms or preprocessing steps.
The pure JavaScript implementation can be slower compared to native or compiled languages when handling extensive data sets.
kNear has a relatively small user base, which may result in fewer community contributions and less comprehensive documentation.
Fit analysis
Who is it for?
✓ Best for
Web developers who need a lightweight, JavaScript-based solution for implementing the k-nearest neighbors algorithm in their applications.
Node.js developers looking for an easy-to-integrate machine learning library without external dependencies.
✕ Not a fit for
Projects requiring complex or advanced machine learning models that go beyond simple classification tasks.
Developers who prefer a more comprehensive ML framework with a wide range of algorithms and features.
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Alternatives
Works well with
Next step
Get Started with kNear
Step-by-step setup guide with code examples and common gotchas.