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where is a model trained using both and.
Therefore, the ANN model trained using the experimental data, was precise enough for predicting the disruption responses.
It is unclear if a model trained using this dataset will yield similar results when evaluated on real world data.
The linear chain CRF model with bigram mode was used, with the model trained using the limited memory BFGS algorithm.
The results show that the Artificial Neural Network model trained using Levenberg Marquardt algorithm has produced more accurate results.
Figure 1 Results obtained on the CHEMDNER test set, using a combination of a first-order and a second-order CRF model, trained using the selected feature set.
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However, data-driven forecasting models trained using the available Big Data may be a possible solution.
Meanwhile, for the experiments using simulated dataset, we experimented on the use of speaker models trained using normalized MFCC only.
For the experiments using real dataset, we experimented on the use of speaker models trained using original MFCC and also normalized MFCC (by CMN).
Increasing the number of models trained using overlapping ranges of C 50 (i.e. MS8, MS11, MS14 and MS18) results in further WER reductions.
Fig. 7 Precision, recall and F-measure values of the models trained using different corpora on the CEMPs, chapati, and BioS patent corpora.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com