ML SIGW0: Difference between revisions
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{{TAGDEF|ML_SIGW0|[real]|1.0}} | {{DISPLAYTITLE:ML_SIGW0}} | ||
{{TAGDEF|ML_SIGW0|[real]|}} | |||
{{DEF|ML_SIGW0|1E-7|for {{TAG|ML_MODE}} {{=}} REFIT|1.0|else}} | |||
Description: This flag sets the | Description: This flag sets the precision parameter <math>s_{\mathrm{w}}</math> (see [[Machine learning force field: Theory#Bayesian linear regression|here]] for definition) for the fitting in the machine learning force field method. | ||
---- | ---- | ||
The default value for {{TAG|ML_MODE}}=''REFIT'' works reliably in most calculations. | |||
However, if the regularization needs to be controlled manually, like e.g. in the fitting via singular value decomposition ({{TAG|ML_MODE}}=''REFIT'' or {{TAG|ML_IALGO_LINREG}}=4), the best is to control the regularization via this parameter and keep the noise paramter <math>s_{\mathrm{v}}</math> (see {{TAG|ML_SIGV0}}) constant at 1. | |||
== Related | For the theory of this regularization parameter see [[Machine learning force field: Theory#Regression|this section]]. | ||
{{TAG|ML_LMLFF}}, {{TAG|ML_IREG}}, {{TAG|ML_SIGV0}} | == Related tags and articles == | ||
{{TAG|ML_LMLFF}}, {{TAG|ML_MODE}}, {{TAG|ML_IREG}}, {{TAG|ML_SIGV0}}, {{TAG|ML_IALGO_LINREG}} | |||
{{sc|ML_SIGW0|Examples|Examples that use this tag}} | {{sc|ML_SIGW0|Examples|Examples that use this tag}} | ||
---- | ---- | ||
[[Category:INCAR]][[Category:Machine | [[Category:INCAR tag]][[Category:Machine-learned force fields]] |
Latest revision as of 17:13, 7 August 2024
ML_SIGW0 = [real]
Default: none
Default: ML_SIGW0 | = 1E-7 | for ML_MODE = REFIT |
= 1.0 | else |
Description: This flag sets the precision parameter (see here for definition) for the fitting in the machine learning force field method.
The default value for ML_MODE=REFIT works reliably in most calculations.
However, if the regularization needs to be controlled manually, like e.g. in the fitting via singular value decomposition (ML_MODE=REFIT or ML_IALGO_LINREG=4), the best is to control the regularization via this parameter and keep the noise paramter (see ML_SIGV0) constant at 1.
For the theory of this regularization parameter see this section.
Related tags and articles
ML_LMLFF, ML_MODE, ML_IREG, ML_SIGV0, ML_IALGO_LINREG