Sentence examples for model training dataset from inspiring English sources

For these experiments, we needed to create three datasets, i.e., speaker model training dataset, NN training dataset, and testing dataset.

Three different datasets were used; the first one for constructing the model (training dataset) and the others for validating the model (external datasets).

The optimum species-specific sensitivity weights were identified using non-linear optimisation, as those that resulted in the highest Spearman's rank correlation coefficient between the Empirically-weighted PSI (E-PSI) scores and deposited fine sediment in the model training dataset.

The empirical data used, comprised observations of invertebrate abundance and percentage fine sediment, collected across a wide range of reference condition temperate stream and river ecosystems (model training dataset n = 2252).

The first step of the ToxCreate workflow enables the user to specify a model training dataset in CSV format, consisting of chemical structures (SMILES) with binary class labels (e.g. active/inactive).

The resulting area under the ROC curve values were 0.770 [95% confidence interval (CI), 0.689 0.850] for the model training dataset and 0.772 955% CI: 0.689 0.856) for the validation dataset, demonstrating high accuracy and generalization ability of the model.

The y-intercept is handled by prepending a column of ones to matrix N. The weights w are solved by

The impairment-factor and quality-based models have been evaluated against the audiovisual subjective test dataset used for developing the model, the "training" dataset, as well as a subjective test dataset not used for training the model, the "evaluation" dataset.

Therefore, for each time interval of model training, the dataset will be different.

In the general case, prior to model training, the dataset is divided into a training set, comprising e.g. 70% of the data, and a test set, which comprises the remaining data.

One of the most important parameters in the performance evaluation of a model is training dataset performance.