GraphCanon updated Sep 30, 2026 · GitHub synced Sep 30, 2026
51views this month
Decision brief
FEDOT: auto-generates ML pipelines using evolutionary algorithms, supports various tasks including classification, regression, clustering, time series prediction.
Good fit when
- For projects requiring automated generative design of machine-learning pipelines suitable for a wide range of tasks and data types
- When an open-source solution is preferred under the BSD-3-Clause license
Avoid when
- In scenarios with strict real-time requirements due to its optimization time
- For environments where only specific ML libraries are acceptable and FEDOT's integrations do not meet those needs
Observed Jul 17, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of Sep 30, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 30, 2026
- Security (OSV)
- 27 low (27 low)
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install FEDOTSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
FEDOT is an AutoML framework for designing machine-learning pipelines using evolutionary algorithms.
Capability facts
- Languages
- python
Source: github.language+pyproject.toml · Sep 30, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Tags
README
.. eng image:: https://img.shields.io/badge/lang en red.svg :target: /README en.rst .. rus image:: https://img.shields.io/badge/lang ru yellow.svg :target: /README.rst .. image:: /docs/fedot logo.png :alt: Logo of FEDOT framework .. start badges .. list table:: :stub columns: 1 p...
For agents
This page has a .md twin and JSON over the API.