ML IREG: Difference between revisions
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{{TAGDEF|ML_FF_IREG_MB|[integer]|2}} | {{TAGDEF|ML_FF_IREG_MB|[integer]|2}} | ||
Description: This tag specifies whether the | Description: This tag specifies whether the regularization parameters are kept constant or not in the machine learning force field method. | ||
---- | ---- | ||
The following cases are possible for this tag: | The following cases are possible for this tag: | ||
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For the optimization of the noise parameter <math>\sigma_{\mathrm{v}}^{2}</math> see following section: | For the optimization of the noise parameter <math>\sigma_{\mathrm{v}}^{2}</math> see following section: | ||
{{TAG| | {{TAG|Machine learning force fields: Theory}}. | ||
== Related Tags and Sections == | == Related Tags and Sections == | ||
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[[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category: | [[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category: Alpha]] |
Revision as of 15:16, 29 February 2020
ML_FF_IREG_MB = [integer]
Default: ML_FF_IREG_MB = 2
Description: This tag specifies whether the regularization parameters are kept constant or not in the machine learning force field method.
The following cases are possible for this tag:
- ML_FF_IREG_MB=1: The (initial) precision (ML_FF_SIGV0_MB) and noise (ML_FF_SIGW0_MB) parameters are kept constant.
- ML_FF_IREG_MB=2: The parameters are optimized (default).
For the optimization of the noise parameter see following section: Machine learning force fields: Theory.
Related Tags and Sections
ML_FF_LMLFF, ML_FF_SIGV0_MB, ML_FF_SIGW0_MB