Comparison
RoBO vs hypertunity
Verdict
Pick RoBO if roBO is a Python framework for robust Bayesian optimization using Gaussian processes and random forests; pick hypertunity if hypertunity is a Python library that facilitates black-box hyperparameter optimisation using techniques such as Bayesian Optimization.
Markdown twin · RoBO alternatives · hypertunity alternatives
GraphCanon updated 2w
Trust & integrity
| Signal | RoBO | hypertunity |
|---|---|---|
| Maintenance | Dormant (2653d since push) As of 2w · github_public_v1 | Dormant (2381d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Personal 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
- RoBO
- A Robust Bayesian Optimization framework
- hypertunity
- A toolset for black-box hyperparameter optimisation
Stars
- RoBO
- 492
- hypertunity
- 137
Forks
- RoBO
- 129
- hypertunity
- 10
Open issues
- RoBO
- 25
- hypertunity
- 0
Language
- RoBO
- Python
- hypertunity
- Python
Adopt for
- RoBO
- RoBO is a Python framework for robust Bayesian optimization using Gaussian processes and random forests.
- hypertunity
- hypertunity is a Python library that facilitates black-box hyperparameter optimisation using techniques such as Bayesian Optimization.
Persona
- RoBO
- -
- hypertunity
- -
Runtime
- RoBO
- -
- hypertunity
- -
License
- RoBO
- BSD-3-Clause
- hypertunity
- Apache-2.0
Last pushed
- RoBO
- Apr 30, 2019
- hypertunity
- Jan 26, 2020
Categories
- RoBO
- Model Training
- hypertunity
- Model Training
Trust and health
Days since push
- RoBO
- 2653d
- hypertunity
- 2381d
Open issues (now)
- RoBO
- 25
- hypertunity
- 0
Owner type
- RoBO
- Organization
- hypertunity
- User
OSV dependency advisories
- RoBO
- Published findings
- hypertunity
- No lockfile (source not queried)
Full report
- RoBO
- Trust report
- hypertunity
- Trust report
Shared compatibility
- Python · RoBO: Python runtime · hypertunity: Python runtime
Choose RoBO if…
- License: RoBO is BSD-3-Clause, hypertunity is Apache-2.0.
- Tags unique to RoBO: gaussian processes, python, random forests.
- For tasks requiring robust handling of noisy data in Bayesian Optimization
When NOT to use RoBO
- Avoid if your project strictly requires open-source licenses other than BSD-3-Clause
- Not suitable for users not comfortable installing external dependencies manually
Choose hypertunity if…
- License: hypertunity is Apache-2.0, RoBO is BSD-3-Clause.
- Requirements: Min 2 GB RAM; Support for SLURM is indicated in the topics, useful for HPC cluster management but not a hard requirement..
- Tags unique to hypertunity: gpyopt, hyperparameter-optimization, slurm, tensorboard.
- When you are working with complex objective functions that are expensive to evaluate, and you need an automated way to optimize your model parameters.
When NOT to use hypertunity
- When the objective function evaluation is inexpensive or fast because hypertunity shines in scenarios where evaluations are costly, offering less benefit if evaluations can be easily repeated.
- If your project does not require advanced techniques such as Bayesian Optimization and you seek a simpler method with fewer dependencies.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (automl/RoBO) · observed Aug 4, 2026
- GitHub forks (automl/RoBO) · observed Aug 4, 2026
- Last push (automl/RoBO) · observed Apr 30, 2019
- License file (BSD-3-Clause) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (gdikov/hypertunity) · observed Aug 4, 2026
- GitHub forks (gdikov/hypertunity) · observed Aug 4, 2026
- Last push (gdikov/hypertunity) · observed Jan 26, 2020
- License file (Apache-2.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: RoBO 492 · hypertunity 137 (synced Aug 4, 2026).
Common questions
- What is the difference between RoBO and hypertunity?
- RoBO: A Robust Bayesian Optimization framework. hypertunity: A toolset for black-box hyperparameter optimisation. See the comparison table for live GitHub stats and shared categories.
- When should I choose RoBO over hypertunity?
- Choose RoBO over hypertunity when License: RoBO is BSD-3-Clause, hypertunity is Apache-2.0; Tags unique to RoBO: gaussian processes, python, random forests; For tasks requiring robust handling of noisy data in Bayesian Optimization.
- When should I choose hypertunity over RoBO?
- Choose hypertunity over RoBO when License: hypertunity is Apache-2.0, RoBO is BSD-3-Clause; Requirements: Min 2 GB RAM; Support for SLURM is indicated in the topics, useful for HPC cluster management but not a hard requirement.; Tags unique to hypertunity: gpyopt, hyperparameter-optimization, slurm, tensorboard; When you are working with complex objective functions that are expensive to evaluate, and you need an automated way to optimize your model parameters.
- When should I avoid RoBO?
- Avoid if your project strictly requires open-source licenses other than BSD-3-Clause Not suitable for users not comfortable installing external dependencies manually
- When should I avoid hypertunity?
- When the objective function evaluation is inexpensive or fast because hypertunity shines in scenarios where evaluations are costly, offering less benefit if evaluations can be easily repeated. If your project does not require advanced techniques such as Bayesian Optimization and you seek a simpler method with fewer dependencies.
- Is RoBO or hypertunity more popular on GitHub?
- RoBO has more GitHub stars (492 vs 137). Stars measure visibility, not whether either tool fits your constraints.
- Are RoBO and hypertunity open source?
- Yes - both are open-source projects on GitHub (RoBO: BSD-3-Clause, hypertunity: Apache-2.0).
- Where can I find alternatives to RoBO or hypertunity?
- GraphCanon lists graph-backed alternatives at RoBO alternatives and hypertunity alternatives (RoBO markdown twin, hypertunity 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, RoBO or hypertunity?
- RoBO: Dormant. hypertunity: Dormant. 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 RoBO and hypertunity?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: RoBO trust report; hypertunity trust report.