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Mostrando ítems 11-20 de 1621
A new SMBO-Based parameter tuning framework to optimization algorithms
(Universidade Federal de Minas GeraisBrasilENG - DEPARTAMENTO DE ENGENHARIA ELÉTRICAPrograma de Pós-Graduação em Engenharia ElétricaUFMG, 2019-11-20)
A variety of algorithms have been proposed by optimization researchers, for solving several different problems. Heuristics and Metaheuristics are two class of algorithms which have been widely used for practical optimization ...
Tuning-aided implicit space mapping
(Int. J. RF and Microwave CAE, 2013)
A Tuning Method for Diatom Segmentation Techniques
(Applied sciences, 2019)
Projeto automático de controlador de velocidade sem sensor mecânico para motores de indução trifásicos
(Universidade Federal de Santa MariaBREngenharia ElétricaUFSMPrograma de Pós-Graduação em Engenharia Elétrica, 2008-08-27)
This works proposes parameters estimation algorithm to auto-tune the control
laws of a speed sensorless servo. The identification process of the electrical and
mechanical parameters is based on recursive least squares ...
Empirical Comparison Of Cross-validation And Internal Metrics For Tuning Svm Hyperparameters
(Elsevier Science BVAmsterdam, 2017)
To tune or not to tune: Recommending when to adjust SVM hyper-parameters via meta-learning
(2015-09-28)
Many classification algorithms, such as Neural Networks and Support Vector Machines, have a range of hyper-parameters that may strongly affect the predictive performance of the models induced by them. Hence, it is recommended ...
Novel Iterative Feedback Tuning Method Based on Overshoot and Settling Time with Fuzzy Logic
(MDPI Open Access Journals, 2023)
To tune or not to tune: recommending when to adjust SVM hyper-parameters via meta-learning
(International Neural Network Society – INNSIEEE Computational Intelligence SocietyKillarney, 2015-07)
Many classification algorithms, such as Neural Networks and Support Vector Machines, have a range of hyperparameters that may strongly affect the predictive performance of the models induced by them. Hence, it is recommended ...
To tune or not to tune: recommending when to adjust SVM hyper-parameters via Meta-learning
(Ieee, 2015-01-01)
Many classification algorithms, such as Neural Networks and Support Vector Machines, have a range of hyperparameters that may strongly affect the predictive performance of the models induced by them. Hence, it is recommended ...
Development of pedotransfer functions for water retention in tropical mountain soil landscapes: spotlight on parameter tuning in machine learning
(2020)
© 2020 Copernicus Gmb H. All rights reserved. Machine-learning algorithms are good at computing non-linear problems and fitting complex composite functions, which makes them an adequate tool for addressing multiple ...