ML CSLOPE: Difference between revisions
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Description: Parameter used in the automatic determination of threshold for Bayesian error estimation in the machine learning force field method. | Description: Parameter used in the automatic determination of threshold for Bayesian error estimation in the machine learning force field method. | ||
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----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 errors is at least twice as large as the slope. We recommend to vary on {{TAG|ML_FF_CSIG}} and keep {{TAG|ML_FF_CSLOPE}} fixed to its default value. | |||
{{TAG| | |||
== Related Tags and Sections == | == Related Tags and Sections == | ||
{{TAG|ML_FF_LMLFF}}, {{TAG|ML_FF_IERR}}, {{TAG|ML_FF_ISAMPLE}}, {{TAG|ML_FF_LCRITERIA}}, {{TAG|ML_FF_CSIG}}, {{TAG|ML_FF_MHIS}} | {{TAG|ML_FF_LMLFF}}, {{TAG|ML_FF_IERR}}, {{TAG|ML_FF_ISAMPLE}}, {{TAG|ML_FF_LCRITERIA}}, {{TAG|ML_FF_CSIG}}, {{TAG|ML_FF_MHIS}} | ||
Revision as of 07:19, 16 April 2021
ML_FF_CSLOPE = [real]
Default: ML_FF_CSLOPE =
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_FF_LCRITERIA first. The parameter ML_FF_CTIFOR is only updated, if the absolute of the slope of the collected Bayesian errors is below ML_FF_CSLOPE times the mean of the collected Bayesian errors. In practice, the slope and the standard errors are correlated, typically the standard errors is at least twice as large as the slope. We recommend to vary on ML_FF_CSIG and keep ML_FF_CSLOPE fixed to its default value.
Related Tags and Sections
ML_FF_LMLFF, ML_FF_IERR, ML_FF_ISAMPLE, ML_FF_LCRITERIA, ML_FF_CSIG, ML_FF_MHIS