Comparison
automl-gs vs metric-learn
Verdict
Pick automl-gs if automl-gs: Python tool for automated machine-learning model creation from CSV data; pick metric-learn if metric-learn is a Python library for metric learning that offers a range of algorithms compatible with scikit-learn's API and supports various methods like LMNN, ITML, LFDA among others.
Markdown twin · automl-gs alternatives · metric-learn alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | automl-gs | metric-learn |
|---|---|---|
| Maintenance | Dormant (2477d since push) As of 2w · github_public_v1 | Slowing (136d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- automl-gs
- Automatically generate machine-learning models and code with input CSV and target field
- metric-learn
- Metric learning algorithms in Python
Stars
- automl-gs
- 1.9k
- metric-learn
- 1.4k
Forks
- automl-gs
- 181
- metric-learn
- 231
Open issues
- automl-gs
- 28
- metric-learn
- 51
Language
- automl-gs
- Python
- metric-learn
- Python
Adopt for
- automl-gs
- automl-gs: Python tool for automated machine-learning model creation from CSV data
- metric-learn
- Metric-learn is a Python library for metric learning that offers a range of algorithms compatible with scikit-learn's API and supports various methods like LMNN, ITML, LFDA among others.
Persona
- automl-gs
- -
- metric-learn
- -
Runtime
- automl-gs
- -
- metric-learn
- -
License
- automl-gs
- MIT
- metric-learn
- MIT
Last pushed
- automl-gs
- Oct 22, 2019
- metric-learn
- Mar 19, 2026
Categories
- automl-gs
- Data & Retrieval, Model Training
- metric-learn
- Model Training
Trust and health
Maintenance
- automl-gs
- Dormant (18%)
- metric-learn
- Slowing (36%)
Days since push
- automl-gs
- 2477d
- metric-learn
- 136d
Open issues (now)
- automl-gs
- 28
- metric-learn
- 51
Owner type
- automl-gs
- User
- metric-learn
- Organization
OSV dependency advisories
- automl-gs
- Published findings
- metric-learn
- No lockfile (source not queried)
Full report
- automl-gs
- Trust report
- metric-learn
- Trust report
Choose automl-gs if…
- Tags unique to automl-gs: automl, keras, tensorflow, xgboost.
- Also covers Data & Retrieval.
- Need to rapidly prototype models with limited ML expertise
When NOT to use automl-gs
- Complex feature engineering or non-standard data inputs required
- Sensitive about licensing of the generated code
Choose metric-learn if…
- Requirements: The application requires Python version 3.6 or higher and specific dependencies such as numpy, scipy, and scikit-learn..
- Tags unique to metric-learn: metric-learning, scikit-learn.
- When you need to use specific metric learning techniques such as Large Margin Nearest Neighbor (LMNN) or Neighborhood Components Analysis (NCA), which are implemented efficiently in Python.
When NOT to use metric-learn
- If your development environment does not already use Python, as metric-learn is specific to this language and its ecosystem.
- For applications that require real-time performance critical operations, since the library may rely on computationally intensive algorithms that could affect latency in real-time systems.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (minimaxir/automl-gs) · observed Aug 4, 2026
- GitHub forks (minimaxir/automl-gs) · observed Aug 4, 2026
- Last push (minimaxir/automl-gs) · observed Oct 22, 2019
- License file (MIT) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (scikit-learn-contrib/metric-learn) · observed Aug 3, 2026
- GitHub forks (scikit-learn-contrib/metric-learn) · observed Aug 3, 2026
- Last push (scikit-learn-contrib/metric-learn) · observed Mar 19, 2026
- License file (MIT) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: automl-gs 1.9k · metric-learn 1.4k (synced Aug 4, 2026).
Common questions
- What is the difference between automl-gs and metric-learn?
- automl-gs: Automatically generate machine-learning models and code with input CSV and target field. metric-learn: Metric learning algorithms in Python. See the comparison table for live GitHub stats and shared categories.
- When should I choose automl-gs over metric-learn?
- Choose automl-gs over metric-learn when Tags unique to automl-gs: automl, keras, tensorflow, xgboost; Also covers Data & Retrieval; Need to rapidly prototype models with limited ML expertise.
- When should I choose metric-learn over automl-gs?
- Choose metric-learn over automl-gs when Requirements: The application requires Python version 3.6 or higher and specific dependencies such as numpy, scipy, and scikit-learn.; Tags unique to metric-learn: metric-learning, scikit-learn; When you need to use specific metric learning techniques such as Large Margin Nearest Neighbor (LMNN) or Neighborhood Components Analysis (NCA), which are implemented efficiently in Python.
- When should I avoid automl-gs?
- Complex feature engineering or non-standard data inputs required Sensitive about licensing of the generated code
- When should I avoid metric-learn?
- If your development environment does not already use Python, as metric-learn is specific to this language and its ecosystem. For applications that require real-time performance critical operations, since the library may rely on computationally intensive algorithms that could affect latency in real-time systems.
- Is automl-gs or metric-learn more popular on GitHub?
- automl-gs has more GitHub stars (1,869 vs 1,438). Stars measure visibility, not whether either tool fits your constraints.
- Are automl-gs and metric-learn open source?
- Yes - both are open-source projects on GitHub (automl-gs: MIT, metric-learn: MIT).
- Where can I find alternatives to automl-gs or metric-learn?
- GraphCanon lists graph-backed alternatives at automl-gs alternatives and metric-learn alternatives (automl-gs markdown twin, metric-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, automl-gs or metric-learn?
- automl-gs: Dormant. metric-learn: Slowing. 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 automl-gs and metric-learn?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: automl-gs trust report; metric-learn trust report.