A machine learning model, neural networek or statistical algorithm will typically have a set of weights or parrameters that are fitted as part of training. Howver, there are also often higher-order parameters that determine the shape or architecture of the model. This may be simple such as the value of 'k' to use in the k-means algorithm, or more complex such as the number of layers, size of each layer and interconnection geometry in a deep neural network.
Used in Chap. 9: page 118
Used in glossary entries: deep neural network, k-means algorithm, machine learning