Side by side
BayesO vs MBPLS
Both stand on statistical analysis software. Which one you can start free with, which one lets you read the code, and what each costs once you pay.
Free plan Linux
BayesO provides a focused Bayesian optimization toolkit with multiple surrogate and acquisition options. Its Linux and Python-package format fit scripting and development workflows, while the examples show machine-learning and WandB applications.
Visit BayesO Free plan Linux
MBPLS combines several multiblock PLS algorithms with fitting, prediction, transformation, and plotting. Its Linux platform and dependency requirements should be checked before installation.
Visit MBPLSThe facts
| BayesO | MBPLS | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | Not published | Not published |
| Runs on | Linux | Linux |
| Lowest paid plan | Free or on request | Not published |
| Plans published | 1 | None |
| Maker | Not published | Not published |
| Website | bayeso.readthedocs.io | mbpls.readthedocs.io |
| On statistical analysis software | #71 of 106 | #67 of 106 |
BayesO: what it does well
- Free MIT-licensed package
- Gaussian process and Student-t surrogates
- Several acquisition-function choices
- Python 3.8 through 3.12 tested
- PyPI and source installation
What to know first
- Linux platform listed
- No free trial
- Optional dependencies require extras
MBPLS: what it does well
- Free Python package
- Supports univariate and multivariate outcomes
- Offers several multiblock algorithms
- Designed to handle missing data
- Includes plotting and block-contribution measures
What to know first
- Linux platform listed
- Sparse data requires NIPALS
- Dependencies may require upgrades