Term #2,249
Training pairs
Claim Term
Training pairs
Origin matter
A method for screening manuscripts
Reference Case 1
BRT_PAT-2-PROV
Date Added
7/14/25
Created
7/14/25, 9:04 PM
Modified
7/14/25, 9:04 PM
Full Desc
“Training pairs” refers to a collection of two-part data structures used to train a machine learning model. Each pair comprises a first component (such as an input, stimulus, or query) and a second component (such as a corresponding label, target output, response, feedback, or the like), which are associated for the purpose of supervised, semi-supervised learning, or the like. Training pairs may be used to teach or train a model to associate certain types of inputs with corresponding outputs by adjusting internal parameters to minimize error between predicted and actual outputs. Examples include, but are not limited to, an image and its category label, a question and its corresponding answer, or a manuscript and a human-generated editorial comment. Training pairs may be represented in structured or unstructured form, may include metadata, and may be stored in databases, files, or serialized objects. (Defined in conjunction with ChatGPT 4o Version, July 14, 2025.)
Applications using this term
| Matter | Usage | Notes | Actions |
|---|---|---|---|
| BRT-PAT-2-PROV | Defined | — | App terms |