like the model no longer respond acuately when initialized and gives an unexpected responce, for ins
like the model no longer respond acuately when initialized and gives an unexpected responce, for instance if the model was used to automate predictive maintenance for small motors it tend to return random feedbacks not according to its trained data and they are most inacurate but if the full model is ran with out pruning its 90% accurate most of the times
