mljar-supervised

Open Source

Explainability and Fairness Updated Feb 15, 2026

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Compared with 13 other Explainability and Fairness agents Open source Self-hostable Updated Feb 2026

💰 Open Source 🔄 Updated Feb 2026 🖥️ Self-hostable

💰 Pricing

Open Source

Pricing not publicly listed.

🎯 Use Cases

Automated feature engineering and model selection for structured datasets Generating interpretable reports for stakeholders Fairness evaluation in classification models Rapid prototyping of ML models for tabular data

⚖️ Pros & Cons

✅ Pros

Comprehensive automation with built-in explainability features
Produces detailed documentation for reproducibility
Supports fairness evaluation to detect biases

❌ Cons

Primarily optimized for tabular data, limiting use with other data types
Less customizable than manual model-building approaches
Performance may lag behind hand-tuned models in specialized domains

Overview

mljar-supervised is an AutoML Python package designed for tabular data, automating tasks like feature engineering, hyperparameter tuning, and model explanations while generating detailed documentation. It emphasizes transparency by providing model interpretability and fairness metrics to aid in decision-making.

Problem It Solves

It simplifies the end-to-end machine learning pipeline for tabular data, reducing manual effort in model selection, optimization, and explanation generation.

Target Audience: Developers and teams working with explainability and fairness 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 mljar-supervised, 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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