Random Decision Forests
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- AT&T,Bell Laboratories
- Organisation type
- Industry,Industry
- Country
- United States of America
- Published
- 14 August 1995
- Authors
- TK Ho
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Other
- Task
- Image classification
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- 60,000 tokens
The images are from the 1992 NIST (National Institute of Standards and Technology) Competition
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Citations
- 4,678
Sources
Where this record came from and when it was last checked.
- Reference
- Random decision forests
- Last updated
- 28 November 2025
What the numbers mean
What this model is
Random Decision Forests was published by AT&T,Bell Laboratories, in United States of America, in August 1995. industry,Industry is the category the publisher falls under.
It works in Other, and is recorded as doing image classification.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Training and provenance
It was trained on about 60,000 tokens of text.
Answers
Random Decision Forests — common questions
How many parameters does Random Decision Forests have?
No parameter count has been published for Random Decision Forests, which is why no memory or speed figure appears on this page.
Who created Random Decision Forests?
Random Decision Forests was published by AT&T,Bell Laboratories, based in United States of America, categorised as industry,Industry.
When was Random Decision Forests released?
Random Decision Forests was published in August 1995. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is Random Decision Forests used for?
Random Decision Forests works in Other, and is recorded as handling image classification. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
What GPU do I need to run Random Decision Forests?
None. Random Decision Forests is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is Random Decision Forests open source?
The licensing for Random Decision Forests was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.