Studies of different kernel functions in nuclear mass predictions with kernel ridge regression
The kernel ridge regression (KRR) approach has been successfully applied in nuclear mass predictions. Kernel function plays an important role in the KRR approach. In this work, the performances of different kernel functions in nuclear mass predictions are carefully explored. The performances are ill...
Main Author: | X. H. Wu |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2023-02-01
|
Series: | Frontiers in Physics |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2023.1061042/full |
Similar Items
-
Nuclear masses in extended kernel ridge regression with odd-even effects
by: X.H. Wu, et al.
Published: (2021-08-01) -
Multi-task learning on nuclear masses and separation energies with the kernel ridge regression
by: X.H. Wu, et al.
Published: (2022-11-01) -
Nuclear Mass Predictions of the Relativistic Density Functional Theory with the Kernel Ridge Regression and the Application to <i>r</i>-Process Simulations
by: Lihan Guo, et al.
Published: (2022-05-01) -
An Ensemble of Kernel Ridge Regression for Multi-class Classification
by: Suganthan, Ponnuthurai Nagaratnam, et al.
Published: (2018) -
Multivariate Information Fusion With Fast Kernel Learning to Kernel Ridge Regression in Predicting LncRNA-Protein Interactions
by: Cong Shen, et al.
Published: (2019-01-01)