tabularfamily
Explainable Boosting Machine (EBM)
Interpretable tabular model from Microsoft's InterpretML library: a boosted generalised additive model whose per-feature contributions can be read directly.
Levelfamily
Classtabular
Parametersnot in the notes
Contextnot in the notes
Releasednot in the notes
Opennessopen source
Runs onnot in the notes
Statusactive
Identity
- Developer
- Microsoft AI
- Family
- not in the notes
- Released
- – sources
- Weights published
- –
- Record checked
- 12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- gradient boosting Glass-box generalised additive model trained with boosting
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- table
- Output
- table
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- open source
- Licence
- MIT License sources
- Access routes
- not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- Part of the InterpretML library (interpretml/interpret, MIT; repository created 3 May 2019).
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
DeveloperMicrosoft AIbig tech, USA
Microsoft AIbig tech, USAModelExplainable Boosting Machine (EBM)Microsoft AI, tabular
Explainable Boosting Machine (EBM)Microsoft AI, tabularUse CasesOil Palm Yield PredictionAgricultureRoute OptimisationRetail and LogisticsUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
PT Astra Agro Lestari TbkIn production, 21 Sep 2026
J&T Express IndonesiaIn production, 26 Aug 2026Unnamed Indonesian estate (15,000 to 17,000 ha)In production, 2024Deployments of these use cases; none names this model.
PT Astra Agro Lestari TbkIn production, 21 Sep 2026J&T Express IndonesiaIn production, 26 Aug 2026Unnamed Indonesian estate (15,000 to 17,000 ha)In production, 2024Deployments of these use cases; none names this model.Organisations 1
Sources
- github.com/interpretml/interpret https://github.com/interpretml/interpret
- auto.gluon.ai/stable/api/autogluon.tabular.models.html https://auto.gluon.ai/stable/api/autogluon.tabular.models.html
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Explainable Boosting Machine (EBM)", https://aurion.semai.id/models/microsoft-ebm/, records of October 2026.