cl-random-forest

Random Forest implementation in Common Lisp for machine learning tasks.

DecliningOpen SourceLow lock-in

Pricing

Free tier

Flat rate

Adoption

Cooling

License

Open Source

Data freshness

Verified · Jul 12, 2026

Overview

What is cl-random-forest?

cl-random-forest is an open-source library that provides a Random Forest algorithm implemented in Common Lisp. It's useful for developers and data scientists who prefer or require the use of Common Lisp for their machine learning projects.

Key differentiator

cl-random-forest stands out as a dedicated Random Forest implementation in Common Lisp, offering developers and researchers an open-source solution within the language ecosystem.

Capability profile

Capability Radar

Ease of StartEcosystemValueMaturityFlexibilityScale Ready

Honest assessment

Strengths & Weaknesses

↑ Strengths

Implementation of the Random Forest algorithm in Common Lisp.medium

Suitable for classification and regression tasks.medium

Open-source with MIT license.medium

↓ Weaknesses

Limited community and supporthigh

Common Lisp is not as widely used as languages like Python or R, leading to a smaller user base and fewer resources for troubleshooting.

Performance limitations compared to optimized implementations in other languagesmedium

While Common Lisp can be efficient, the performance of cl-random-forest might not match highly optimized libraries written in C or specialized machine learning frameworks like scikit-learn.

Limited integrations with popular data science tools and platformsmedium

Common Lisp has fewer ecosystem integrations compared to languages such as Python, which has extensive support for various data processing and visualization libraries.

Fit analysis

Who is it for?

✓ Best for

Common Lisp developers who need a robust implementation of Random Forest for their projects.

Educators and students learning about ensemble methods in machine learning using Common Lisp.

✕ Not a fit for

Projects requiring high performance or scalability beyond what can be achieved with Common Lisp.

Developers preferring languages other than Common Lisp for machine learning tasks.

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

Next step

Get Started with cl-random-forest

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →