Sentence examples for models with fewer from inspiring English sources

Throw-away cameras, auto-focus and digital models with fewer movable (hence breakable) parts, took a toll on the business.

Models with fewer parameters are therefore preferred on the grounds of parsimony.

Objective functions such as this quickly force models into a reduced feature space by favouring models with fewer descriptors.

In this paper, a basis pursuit approach is employed using the LASSO algorithm to reduce the complexity of the mitigation technique yielding models with fewer number of coefficients that keep limited modeling error.

However, the moving probabilities used to choose descriptors will be misleading as they will largely be based on those descriptors present in models with fewer descriptors rather than those with the best predictive ability.

When compared to the use of a genetic algorithm for optimising the feature selection of a PLS model, the WAAC algorithm performs well, both in terms of faster convergence and in its ability to produce models with fewer descriptors.

However, these works often assume speaker-dependent models with few target speakers that are known during training.

The development of initial prediction models with few independent variables (one to two at most), also helps to obtain more trustful models when few data is available.

However, they contributed in a reduced form to the regression models due to multicollinearity problems, which resulted in final regression models with few significant explanatory variables (Table 5).

Simple models with few parameters seldom can describe the real complexity of the phenomena arising during the heating of the various substances.

In many hybrid simulations, including those that have used UI-SimCor, analytical models with few effective degrees of freedom are typically used.