ML CSLOPE: Difference between revisions

Revision as of 08:16, 23 August 2021

ML_CSLOPE = [real]
Default: ML_CSLOPE = $0.2$

Description: Parameter used in the automatic determination of threshold for Bayesian error estimation in the machine learning force field method.

For details please read entry ML_LCRITERIA first. The parameter ML_CTIFOR is only updated, if the absolute of the slope of the collected Bayesian errors is below ML_CSLOPE times the mean of the collected Bayesian errors. In practice, the slope and the standard errors are correlated: typically the standard error is at least twice the slope. We recommend to vary only ML_CSIG and keep ML_CSLOPE fixed to its default value.

Related Tags and Sections

ML_LMLFF, ML_ICRITERIA, ML_CSIG, ML_MHIS

Examples that use this tag

@@ Line 1: / Line 1: @@
-{{TAGDEF|ML_FF_CSLOPE|[real]|<math>0.2</math>}}
+{{TAGDEF|ML_CSLOPE|[real]|<math>0.2</math>}}
 Description: Parameter used in the automatic determination of threshold for Bayesian error estimation in the machine learning force field method.
 ----
-----For details please read entry {{TAG|ML_FF_LCRITERIA}} first. The parameter {{TAG|ML_FF_CTIFOR}} is only updated, if the absolute of the slope of the collected Bayesian errors is below {{TAG|ML_FF_CSLOPE}} times the mean of the collected Bayesian errors. In practice, the slope and the standard errors are correlated: typically the standard error is at least twice the slope. We recommend to vary only {{TAG|ML_FF_CSIG}} and keep {{TAG|ML_FF_CSLOPE}} fixed to its default value.
+----For details please read entry {{TAG|ML_LCRITERIA}} first. The parameter {{TAG|ML_CTIFOR}} is only updated, if the absolute of the slope of the collected Bayesian errors is below {{TAG|ML_CSLOPE}} times the mean of the collected Bayesian errors. In practice, the slope and the standard errors are correlated: typically the standard error is at least twice the slope. We recommend to vary only {{TAG|ML_CSIG}} and keep {{TAG|ML_CSLOPE}} fixed to its default value.
 == Related Tags and Sections ==
-{{TAG|ML_FF_LMLFF}}, {{TAG|ML_FF_LCRITERIA}}, {{TAG|ML_FF_CSIG}}, {{TAG|ML_FF_MHIS}}
+{{TAG|ML_LMLFF}}, {{TAG|ML_ICRITERIA}}, {{TAG|ML_CSIG}}, {{TAG|ML_MHIS}}
-{{sc|ML_FF_CSLOPE|Examples|Examples that use this tag}}
+{{sc|ML_CSLOPE|Examples|Examples that use this tag}}
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 [[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category: Alpha]]