cl-random-forest

Open Source

Common Lisp Updated Feb 15, 2026

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Compared with 4 other Common Lisp agents Open source Self-hostable Updated Feb 2026

💰 Open Source 🔄 Updated Feb 2026 🖥️ Self-hostable

💰 Pricing

Open Source

Pricing not publicly listed.

🎯 Use Cases

Classification tasks in Common Lisp applications Regression analysis for research projects Educational tool for learning Random Forest algorithms in Lisp Prototyping ML models in Lisp before production deployment

⚖️ Pros & Cons

✅ Pros

Native Common Lisp implementation avoids foreign language dependencies
Open-source and self-hostable for full control
Lightweight and integrable into Lisp workflows

❌ Cons

Likely slower than optimized C/Python implementations
Smaller community compared to mainstream ML libraries
Limited documentation and examples compared to popular alternatives

Overview

cl-random-forest is a Common Lisp implementation of the Random Forest machine learning algorithm, designed for classification and regression tasks. It provides a Lisp-native way to train and deploy ensemble models using decision trees.

Problem It Solves

Enables Common Lisp developers to perform robust machine learning tasks without relying on external libraries or languages.

Target Audience: Developers and teams working with common lisp automation.

Inputs

• User configuration
• API credentials (if required)
• Task parameters

Outputs

• Automated task results
• Status reports
• Generated content or actions

Example Workflow

1 User configures the agent with required parameters
2 Agent receives input data or trigger
3 Agent processes the request using its core logic
4 Agent interacts with external services if needed
5 Results are returned to the user

Sample System Prompt


              You are cl-random-forest, an AI assistant. Help the user accomplish their task efficiently.

Tools & Technologies

LLM APIs Python

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FAQs

Is this agent open-source?: Yes
Can this agent be self-hosted?: Yes
What skill level is required?: Intermediate

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