Semigetrainde

Semigetrainde is a term encountered primarily in Dutch-language technical discussions to describe a state of a system that has been trained only partially. The word is formed from semi- (half) and getrainde (trained), with getrainde being the past participle of trainen (to train). There is no single formal definition recognized across disciplines, and the term tends to be used informally to signal partial or staged training rather than a standardized phase in a process.

In machine learning and artificial intelligence, semigetrainde models are typically those where training is intentionally bounded by constraints such as limited data, reduced feature sets, early stopping, or staged training regimes. Such approaches may be used during prototyping, curriculum learning, or transfer learning, where a model is first trained on general tasks or data before adapting to a narrower domain. In this sense, semigetrainde models aim to balance development speed, resource use, and potential overfitting.

Limitations include the risk of underfitting, inconsistent performance, or difficulties in comparing with fully trained baselines. The term's informal nature means that its exact meaning can vary between teams or publications; explicit documentation of training scope and criteria is recommended when using the label semigetrainde.

See also: partial training, early stopping, transfer learning, curriculum learning.