Sentence examples for by combining different models from inspiring English sources

First, in recent years, there has a growing number of studies investigating the impact of using combination theory on forecasting accuracy; their objective is to enhance forecasting accuracy by combining different models.

The idea is aimed at improving predictive capability of a data-driven model by combining different models within a composite data-driven model.

As the most predictive PCM model exhibited moderately high (R^{2}_{0 test}) and (q^{2}_{textit {test}}) values, as well as moderately low RMSEtest values (Table 2A and Figure 4), we explored the possibility of enhancing model performance by combining different models into a more predictive model ensemble (Table 2D, E and Figure 4).

In other words, all characteristics of underlying data cannot be fully modeled by one model and therefore, combining different models or using hybrid ones helps analyze complex patterns in data more accurately and completely.

The term bagging refers to a class of techniques in which an ensemble model is obtained by combining different member models generated by resampling the available data set.

The Oulu researchers suggest that even further increases in efficiency may be possible, since they can take the work they've done mimicking natural light-gathering surfaces and try to "exceed the results of evolution" by combining different applicable models.

To validate the effectiveness of the proposed method, experiments are conducted in which human faces are detected and localized in images by combining different face models.

Results, which were interpreted by combining different analysis models, showed that the effectiveness of nano-modification is strictly influenced by the combination of base binder, additive type and dosage.

As indicated above, some of the discussed caveats may be partly overcome by combining different alternative models in an intelligent testing strategy.

We were able to improve the in silico inventory of A. niger secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models.

Taken together, these results indicate that higher predictive power can be obtained when modelling this dataset by combining different single QSPR models with either greedy optimisation or model stacking.