Algoritmos de ensembles para problemas de salidas múltiples, nuevos desarrollos y aplicaciones

Artículo

1. Improving the accuracy of machine-learning models with data from machine test repetitions 2022

   Journal of Intelligent Manufacturing

2. Rotation Forest for multi-target regression 2022

   International Journal of Machine Learning and Cybernetics

3. High-accuracy classification of thread quality in tapping processes with ensembles of classifiers for imbalanced learning 2021

   Measurement: Journal of the International Measurement Confederation

4. Machine-learning for automatic prediction of flatness deviation considering the wear of the face mill teeth 2021

   Journal of Intelligent Manufacturing

5. Rotation forest for big data 2021

   Information fusion

6. Using ensembles for accurate modelling of manufacturing processes in an IoT data-acquisition solution 2020

   Applied Sciences (Switzerland)

7. An experimental evaluation of mixup regression forests 2020

   Expert Systems with Applications

8. Early and extremely early multi-label fault diagnosis in induction motors 2020

   ISA Transactions

9. Random Balance ensembles for multiclass imbalance learning 2020

   Knowledge-Based Systems

10. You Are Not My Type: An Evaluation of Classification Methods for Automatic Phytolith Identification 2020

    Microscopy and Microanalysis