Sentence examples for model complexity are from inspiring English sources

Together with the performance figures of interest, methodological issues concerning the choice of the most appropriate model abstraction level, the adoption of a compositional modelling approach, and the management of the model complexity are also discussed.

Three techniques in increasing order of model complexity are discussed.

In this approach, increasing levels of model complexity are used and various thermal targets are set and implemented.

The number of patterns which represents the model complexity are determined by Bayesian Information Criteria (BIC), while other parameters of GMM are estimated by using Expectation-Maximization algorithm under the Maximum Likelihood criteria, based on the monitored cable tension force.

Two hybrid DNN-HMM and four GMM-HMM back-end systems of increasing acoustic model complexity are trained.

(c) Model complexity was chosen according to Cross-Validation (CV) Median Squared Error (MSE).

The model complexity is increased stepwise by adding components to an existing 2D overland flow model.

The model complexity was reduced by ignoring the spatial variations and assuming isothermal stack operation.

By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps.

Probabilistic context-free grammars (PCFGs) have played an important role in the modeling of syntax in natural language processing and other applications, but choosing the proper model complexity is often difficult.

Furthermore, the optimized pretreatment methods and wavelength variables are more reasonable, the model complexity is smaller, and the model robustness is stronger than other relative methods.