Sentence examples for model training with from inspiring English sources

G. Kurata, A. Sethy, B. Ramabhadran, A. Rastrow, N. Itoh and M. Nishimura "Acoustically discrim- inative language model training with pseudo-hypothesis", Speech Communication, Volume 5, Issue 2, pages 219-228, 2011.

In the hybrid-6 model, training with information from both – the PSSM and secondary structure information as input to the classifier enhances both the prediction accuracy and reliability of the models generated.

See Figure 6 for an example illustrating how model training with W2V is carried out.

All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training.

All six combinations of five groups were used for model training, with cross-validation performed by predicting each group not used in training.

Therefore, it is important to generate a growing database for model training, with corresponding sets of genotypes for the breeding program and target environments and continually increase the number of environments tested.

Among the developed models, performance of neural network model trained with particle swarm optimization model is superior in terms of computational speed and accuracy.

It is concluded that the feed-forward neural network (FF-NN) model trained with BA outperforms the other models with better prediction results.

The ANFIS model trained with the input data vector including previous inflows and cyclic terms of monthly periodicity has shown a significant improvement in the forecast accuracy in comparison with the ANFIS models trained with the input vectors considering only previous inflows.

It is found that neural net work model trained with particle swarm optimization technique performs better comparable to other developed neural network models.

And then, the SVM fire risk assessment model trained with the sample data was used for the fire risk assessment of a sports architecture.