ML IREG: Difference between revisions

Revision as of 08:45, 23 August 2021

ML_IREG = [integer]
Default: ML_IREG = 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_IREG=1: The (initial) precision (ML_SIGV0) and noise (ML_SIGW0) parameters are kept constant.
ML_IREG=2: The parameters are optimized (default).

For the optimization of the noise parameter $\sigma_{\mathrm{v}}^{2}$ see following section: Machine learning force fields: Theory.

@@ Line 1: / Line 1: @@
-{{TAGDEF|ML_FF_IREG_MB|[integer]|2}}
+{{TAGDEF|ML_IREG|[integer]|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:
-*{{TAG|ML_FF_IREG_MB}}=1: The (initial) precision ({{TAG|ML_FF_SIGV0_MB}}) and noise ({{TAG|ML_FF_SIGW0_MB}}) parameters are kept constant.
+*{{TAG|ML_IREG}}=1: The (initial) precision ({{TAG|ML_SIGV0}}) and noise ({{TAG|ML_SIGW0}}) parameters are kept constant.
-*{{TAG|ML_FF_IREG_MB}}=2: The parameters are optimized (default).
+*{{TAG|ML_IREG}}=2: The parameters are optimized (default).
 For the optimization of the noise parameter <math>\sigma_{\mathrm{v}}^{2}</math> see following section:
@@ Line 11: / Line 11: @@
 == Related Tags and Sections ==
-{{TAG|ML_FF_LMLFF}}, {{TAG|ML_FF_SIGV0_MB}}, {{TAG|ML_FF_SIGW0_MB}}
+{{TAG|ML_LMLFF}}, {{TAG|ML_SIGV0}}, {{TAG|ML_SIGW0}}
-{{sc|ML_FF_IREG_MB|Examples|Examples that use this tag}}
+{{sc|ML_IREG|Examples|Examples that use this tag}}
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 [[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category: Alpha]]