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models optimization » model optimization (Expand Search), process optimization (Expand Search), wolf optimization (Expand Search)
code optimization » codon optimization (Expand Search), model optimization (Expand Search), dose optimization (Expand Search)
primary scale » primary staple (Expand Search), primary care (Expand Search), primary case (Expand Search)
scale models » scale model (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data code » data model (Expand Search), data came (Expand Search)
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DataSheet1_Optimal capacity configuration of the wind-storage combined frequency regulation system considering secondary frequency drop.docx
Published 2023“…The optimization model is solved by the multi-objective salp swarm algorithm (MSSA) to obtain the setting value of wind-storage combined frequency regulation parameters and the optimal energy storage capacity. …”
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<b>Spatial modeling of gully density on the Qinghai-Tibet Plateau: Application of hyperparameter optimization in interpretable machine learning</b>
Published 2025“…Various machine learning models were used, and different hyperparameter optimization algorithms were selected to train the models to obtain the best model. …”
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Table_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.xlsx
Published 2021“…The optimal ML model was selected to be DAMS. In addition, SHapley Additive exPlanations (SHAP) approach was introduced to rank the feature importance. …”
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Data_Sheet_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.docx
Published 2021“…The optimal ML model was selected to be DAMS. In addition, SHapley Additive exPlanations (SHAP) approach was introduced to rank the feature importance. …”
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Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish)
Published 2024“…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …”
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