Decision tree adaline
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
- Tokyo Medical and Dental University
- Organisation type
- Academia
- Country
- Japan
- Published
- 1 May 1969
- Authors
- T Sano, S Tsuchiya, F Suzuki
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Medicine
- Task
- Medical diagnosis
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.
- Parameters
- 2.5K
- Training data
- tokens
5 adaline were trained on binary decisions (p. 1) Each adaline had up to 490 input weights (“meshes”) Total parameters = 5*490=2450
40 positive and negative training examples (p. 2)
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- Historical significance
- Record confidence
- Confident
Sources
Where this record came from and when it was last checked.
- Reference
- A use of Adaline as an automatic method for interpretation of the electrocardiogram and the vectorcardiogram
- Last updated
- 28 November 2025
What the numbers mean
What this model is
Decision tree adaline was published by Tokyo Medical and Dental University, in Japan, in May 1969. academia is the category the publisher falls under.
It works in Medicine, and is recorded as doing medical diagnosis.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
What went into building it
It is tracked in the underlying dataset for one reason in particular: historical significance.
Answers
Decision tree adaline — common questions
How many parameters does Decision tree adaline have?
Decision tree adaline has 2.5K parameters. 5 adaline were trained on binary decisions (p. 1) Each adaline had up to 490 input weights (“meshes”) Total parameters = 5*490=2450. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
Who created Decision tree adaline?
Decision tree adaline was published by Tokyo Medical and Dental University, based in Japan, categorised as academia.
When was Decision tree adaline released?
Decision tree adaline was published in May 1969. 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 Decision tree adaline used for?
Decision tree adaline works in Medicine, and is recorded as handling medical diagnosis. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run Decision tree adaline?
None. Decision tree adaline 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 Decision tree adaline open source?
The licensing for Decision tree adaline 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.