https://github.com/ahmed-bayoumy/slml

Statistical learning models library for blackbox optimization
https://github.com/ahmed-bayoumy/slml

blackbox-optimization derivative-free-optimization multidisciplinary-design-optimization multidisciplinary-optimization multimodel-management relative-adequacy-framework surrogate surrogate-based-optimization surrogate-model-based-optimization surrogate-modelling surrogate-models

Last synced: 5 months ago
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Statistical learning models library for blackbox optimization

• Host: GitHub
• URL: https://github.com/ahmed-bayoumy/slml
• Owner: Ahmed-Bayoumy
• License: lgpl-2.1
• Created: 2022-04-16T16:16:11.000Z (about 4 years ago)
• Default Branch: DEV
• Last Pushed: 2023-12-25T05:11:07.000Z (over 2 years ago)
• Last Synced: 2025-11-08T11:21:10.773Z (7 months ago)
• Topics: blackbox-optimization, derivative-free-optimization, multidisciplinary-design-optimization, multidisciplinary-optimization, multimodel-management, relative-adequacy-framework, surrogate, surrogate-based-optimization, surrogate-model-based-optimization, surrogate-modelling, surrogate-models
• Language: Python
• Homepage:
• Size: 1.95 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# SLML

Statistical Learning Models Library: A python library for dynamic surrogates and statistical learning algorithms

**Version 2.1.0**

---

## License & copyright

© Ahmed H. Bayoumy 

---

## Installation

`pip install StatLML`

## How to use SLML package

After installing the `SLML` package, the functions and classes of `SLML` module can be imported directly into the python script as follows:

```pycon

from SLML import *

```