Publication date
November 2022
DOIAbstract
Dataset that is used for training the model. Comprises all the variables used in the model and also the corresponding target.</p
Dataset that is used for training the model. Comprises all the variables used in the model and also the corresponding target.</p
Parameter of the variogram models of the transformed regression residuals for each indicator.</p
The data provided here are part of a Galaxy Training Network tutorial for "Machine learning: classif...
model weights used in the experiment. InceptionResnetV2, MobilenetV2, Resnet50V5, Resnet152 and Xcep...
<p>This dataset was used to create the predictive model applied to all other datasets.</p
Description of the data transformation methods for compositional data and forecasting models.</p
Model variables and input variables (external inputs) along with their unit of measurement and descr...
Datasets (systems and benchmarks) used in the selected studies to train RNN models.</p
Setting training, validation and testing dataset during the whole sample period.</p
The evaluation results based on four pretraining language models for two datasets.</p
<p>Model parameters and values used for the fit in our experimental conditions.</p
<p>a) Model set; b) Data set; c) Model & Transformed Data; d) Model & Transformed Data after registr...
<p>Training gain for each predictor variable alone (black) and the loss in training gain when the va...
Regression model Input variables and resulting regression coefficients by cluster for the calibratio...
<p>A Statistical model comparison in training the models when P = 105 and Q = 27.</p
<p>Overview over datasets with training and test data used in the competition.</p
Parameter of the variogram models of the transformed regression residuals for each indicator.</p
The data provided here are part of a Galaxy Training Network tutorial for "Machine learning: classif...
model weights used in the experiment. InceptionResnetV2, MobilenetV2, Resnet50V5, Resnet152 and Xcep...
<p>This dataset was used to create the predictive model applied to all other datasets.</p
Description of the data transformation methods for compositional data and forecasting models.</p
Model variables and input variables (external inputs) along with their unit of measurement and descr...
Datasets (systems and benchmarks) used in the selected studies to train RNN models.</p
Setting training, validation and testing dataset during the whole sample period.</p
The evaluation results based on four pretraining language models for two datasets.</p
<p>Model parameters and values used for the fit in our experimental conditions.</p
<p>a) Model set; b) Data set; c) Model & Transformed Data; d) Model & Transformed Data after registr...
<p>Training gain for each predictor variable alone (black) and the loss in training gain when the va...
Regression model Input variables and resulting regression coefficients by cluster for the calibratio...
<p>A Statistical model comparison in training the models when P = 105 and Q = 27.</p
<p>Overview over datasets with training and test data used in the competition.</p
Parameter of the variogram models of the transformed regression residuals for each indicator.</p
The data provided here are part of a Galaxy Training Network tutorial for "Machine learning: classif...
model weights used in the experiment. InceptionResnetV2, MobilenetV2, Resnet50V5, Resnet152 and Xcep...
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