Definition: Unostensive is a concept in computer science, specifically in the field of machine learning and neural networks. It refers to the situation where a model or algorithm performs poorly on both training data and unseen test data due to insufficiently complex or optimized hyperparameters. In other words, if a model has a high number of parameters that are not being used effectively during training (i.e., unoptimized), it might struggle to learn from new data. This can lead to poor performance in terms of accuracy on