ML SIGV0: Difference between revisions

Revision as of 15:43, 3 July 2023

ML_SIGV0 = [real]
Default: ML_SIGV0 = 1.0

Description: This flag sets the noise parameter $s_{\mathrm {v} }$ for the fitting in the machine learning force field method.

If the regularization needs to be controlled manually, like e.g. in the fitting via singular value decomposition (ML_IALGO_LINREG=4), the best is to keep this parameter constant at 1 and control the regularization via the precision parameter $s_{\mathrm {w} }$ (see ML_SIGW0.

For the theory of this regularization parameter see this section.

Related tags and sections

ML_LMLFF, ML_IREG, ML_SIGW0

Examples that use this tag

@@ Line 4: / Line 4: @@
 Description: This flag sets the noise parameter <math>s_{\mathrm{v}}</math> for the fitting in the machine learning force field method.
 ----
-For details about the optimization of this regularization parameter see [[Machine learning force field: Theory#Bayesian error estimation|this section]].
+If the regularization needs to be controlled manually, like e.g. in the fitting via singular value decomposition ({{TAG|ML_IALGO_LINREG}}=4), the best is to keep this parameter constant at 1 and control the regularization via the precision parameter <math>s_{\mathrm{w}}</math> (see {{TAG|ML_SIGW0}}.
+For the theory of this regularization parameter see [[Machine learning force field: Theory#Regression|this section]].
 == Related tags and sections ==