SAM_MachineLearning is part of the SAM (Sustainable Analytical Model) Toolkit —
an open-source collection of tools designed to help engineers create, manage,
and process analytical building models for energy and environmental analysis.
This repository is dedicated to experimental work and prototyping involving machine learning within the SAM ecosystem. It provides a sandbox for exploring data-driven methods, learning-based models, and hybrid analytical–machine-learning workflows applied to building performance analysis.
The content of this repository may evolve rapidly and is intended primarily for research, experimentation, and proof-of-concept development.
Typical areas of investigation include:
- application of machine learning to SAM analytical data
- surrogate and reduced-order models
- pattern recognition and clustering in simulation results
- hybrid workflows combining physics-based models and ML approaches
The repository does not represent a stable API and may change as experiments progress.
- 📘 SAM Wiki: https://github.com/SAM-BIM/SAM/wiki
- 🧠 SAM Core: https://github.com/SAM-BIM/SAM
- 🧰 Installers: https://github.com/SAM-BIM/SAM_Deploy
- Target framework: .NET / C# (additional tools or languages may be explored)
- Experimental code may not follow full SAM module conventions
- New or modified
.csfiles must include the SPDX header fromCOPYRIGHT_HEADER.txt
This repository is free software licensed under the
GNU Lesser General Public License v3.0 or later (LGPL-3.0-or-later).
Each contributor retains copyright to their respective contributions.
The project history (Git) records authorship and provenance of all changes.
See:
LICENSENOTICECOPYRIGHT_HEADER.txt