Comparison
auto-sklearn vs scikit-learn
Verdict
Coexists - Both coexist in ecosystem; Auto-sklearn simplifies complex configurations but not all features are included.
Markdown twin · auto-sklearn alternatives · scikit-learn alternatives
GraphCanon updated today
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Trust & integrity
| Signal | auto-sklearn | scikit-learn |
|---|---|---|
| Maintenance | Active (12d since push) As of 5d · github_public_v1 | Very active (0d since push) As of 5d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 5d · github_public_v1 | Not a fork · Organization account As of 5d · github_public_v1 |
| OSV dependency advisories | Published findings As of 5d · osv@v1 | No lockfile (source not queried) As of 5d · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- auto-sklearn
- Automated Machine Learning with scikit-learn
- scikit-learn
- machine learning in Python
Stars
- auto-sklearn
- 8.1k
- scikit-learn
- 67k
Forks
- auto-sklearn
- 1.3k
- scikit-learn
- 27k
Open issues
- auto-sklearn
- 210
- scikit-learn
- 2.1k
Language
- auto-sklearn
- Python
- scikit-learn
- Python
Adopt for
- auto-sklearn
- auto-sklearn is an automated machine learning toolkit designed to automate hyperparameter optimization and function seamlessly with scikit-learn workflows.
- scikit-learn
- Use scikit-learn for Python-based machine learning tasks that require robust algorithms, comprehensive documentation, and extensive community support.
Persona
- auto-sklearn
- -
- scikit-learn
- -
Runtime
- auto-sklearn
- -
- scikit-learn
- -
License
- auto-sklearn
- BSD-3-Clause
- scikit-learn
- BSD-3-Clause
Last pushed
- auto-sklearn
- Jun 29, 2026
- scikit-learn
- Jul 11, 2026
Categories
- auto-sklearn
- Model Training
- scikit-learn
- Model Training
Trust and health
Maintenance
- auto-sklearn
- Active (82%)
- scikit-learn
- Very active (96%)
Days since push
- auto-sklearn
- 12d
- scikit-learn
- 0d
Open issues (now)
- auto-sklearn
- 210
- scikit-learn
- 2.1k
OSV dependency advisories
- auto-sklearn
- Published findings
- scikit-learn
- No lockfile (source not queried)
Full report
- auto-sklearn
- Trust report
- scikit-learn
- Trust report
Typed relationship
auto-sklearn successor scikit-learnAuto-Sklearn builds upon scikit-learn to offer automated machine learning, providing a higher-level abstraction that simplifies the process of using and integrating with scikit-learn models.Coexists - Both coexist in ecosystem; Auto-sklearn simplifies complex configurations but not all features are included.
Shared compatibility
- Python · auto-sklearn: Python runtime · scikit-learn: Python runtime
Choose auto-sklearn if…
- Auto-Sklearn builds upon scikit-learn to offer automated machine learning, providing a higher-level abstraction that simplifies the process of using and integrating with scikit-learn models.
- Tags unique to auto-sklearn: automated-machine-learning, automl, bayesian-optimization, hyperparameter-optimization.
- auto-sklearn ships Docker support for self-hosted deployment.
- When you need a drop-in replacement estimator for your existing scikit-learn pipeline that can handle the complexity of hyperparameter tuning automatically.
When NOT to use auto-sklearn
- If extensive customization or control over individual machine learning components is required beyond what auto-sklearn's automation offers.
- In cases requiring non-scikit-learn model ensembles, as the toolkit primarily supports models that are part of the scikit-earn library.
Choose scikit-learn if…
- Auto-Sklearn builds upon scikit-learn to offer automated machine learning, providing a higher-level abstraction that simplifies the process of using and integrating with scikit-learn models.
- Tags unique to scikit-learn: data-analysis, data-science, machine-learning, python.
- When you need a well-documented library with clear examples and strong community support.
When NOT to use scikit-learn
- Avoid if you require cutting-edge deep learning capabilities or model training that is more efficiently managed with GPU accelerators.
- Not ideal when dealing with very large datasets that benefit from out-of-core computation, as it lacks native support for such functionalities.
- If real-time machine learning predictions are critical and need ultra-low latency, other tools might offer better performance.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (automl/auto-sklearn) · observed Jul 11, 2026
- GitHub forks (automl/auto-sklearn) · observed Jul 11, 2026
- Last push (automl/auto-sklearn) · observed Jun 29, 2026
- License file (BSD-3-Clause) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (scikit-learn/scikit-learn) · observed Jul 11, 2026
- GitHub forks (scikit-learn/scikit-learn) · observed Jul 11, 2026
- Last push (scikit-learn/scikit-learn) · observed Jul 11, 2026
- License file (BSD-3-Clause) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: auto-sklearn 8.1k · scikit-learn 67k (synced Jul 11, 2026).
Common questions
- What is the difference between auto-sklearn and scikit-learn?
- auto-sklearn: Automated Machine Learning with scikit-learn. scikit-learn: machine learning in Python. See the comparison table for live GitHub stats and shared categories.
- When should I choose auto-sklearn over scikit-learn?
- Choose auto-sklearn over scikit-learn when Auto-Sklearn builds upon scikit-learn to offer automated machine learning, providing a higher-level abstraction that simplifies the process of using and integrating with scikit-learn models; Tags unique to auto-sklearn: automated-machine-learning, automl, bayesian-optimization, hyperparameter-optimization; auto-sklearn ships Docker support for self-hosted deployment; When you need a drop-in replacement estimator for your existing scikit-learn pipeline that can handle the complexity of hyperparameter tuning automatically.
- When should I choose scikit-learn over auto-sklearn?
- Choose scikit-learn over auto-sklearn when Auto-Sklearn builds upon scikit-learn to offer automated machine learning, providing a higher-level abstraction that simplifies the process of using and integrating with scikit-learn models; Tags unique to scikit-learn: data-analysis, data-science, machine-learning, python; When you need a well-documented library with clear examples and strong community support.
- When should I avoid auto-sklearn?
- If extensive customization or control over individual machine learning components is required beyond what auto-sklearn's automation offers. In cases requiring non-scikit-learn model ensembles, as the toolkit primarily supports models that are part of the scikit-earn library.
- When should I avoid scikit-learn?
- Avoid if you require cutting-edge deep learning capabilities or model training that is more efficiently managed with GPU accelerators. Not ideal when dealing with very large datasets that benefit from out-of-core computation, as it lacks native support for such functionalities. If real-time machine learning predictions are critical and need ultra-low latency, other tools might offer better performance.
- Is auto-sklearn or scikit-learn more popular on GitHub?
- scikit-learn has more GitHub stars (66,693 vs 8,119). Stars measure visibility, not whether either tool fits your constraints.
- Are auto-sklearn and scikit-learn open source?
- Yes - both are open-source projects on GitHub (auto-sklearn: BSD-3-Clause, scikit-learn: BSD-3-Clause).
- Where can I find alternatives to auto-sklearn or scikit-learn?
- GraphCanon lists graph-backed alternatives at auto-sklearn alternatives and scikit-learn alternatives (auto-sklearn markdown twin, scikit-learn markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, auto-sklearn or scikit-learn?
- auto-sklearn: Active. scikit-learn: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for auto-sklearn and scikit-learn?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: auto-sklearn trust report; scikit-learn trust report.