Prediction of the critical temperature of a superconductor by using the WOA/MARS, Ridge, Lasso and Elastic-net machine learning techniques.
Paulino José García NietoEsperanza García GonzaloJosé Pablo Paredes-SánchezPublished in: Neural Comput. Appl. (2021)
Keyphrases
- elastic net
- topology preserving
- prediction accuracy
- linear support vector machines
- machine learning
- prediction model
- neural network
- machine learning algorithms
- kernel learning
- regularized regression
- multiple kernel learning
- regularization parameter
- boundary conditions
- level set method
- magnetic field
- supervised learning
- least squares
- feature extraction