trainingbased
Trainingbased is a term used to describe strategies, systems, or pipelines in which the training phase is central to achieving and maintaining performance. In machine learning, this often means giving primary importance to the collection, labeling, preprocessing, and iterative updating of training data, as opposed to relying primarily on architectural novelty or post-training adjustments at deployment. The term is not universally standardized and may be used differently across domains, but it generally signals that training dynamics are the main lever for capability and reliability.
In practice, trainingbased approaches include supervised learning, self-supervised learning, and continual or online learning, where models
Advantages of trainingbased methods include the potential for performance gains as data quality improves, clearer attribution
See also: machine learning, data versioning, continual learning, model retraining.