ML CSLOPE: Difference between revisions
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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 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_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. | ||
== Related Tags and Sections == | == Related Tags and Sections == | ||
{{TAG|ML_FF_LMLFF | {{TAG|ML_FF_LMLFF}}, {{TAG|ML_FF_ISAMPLE}}, {{TAG|ML_FF_LCRITERIA}}, {{TAG|ML_FF_CSIG}}, {{TAG|ML_FF_MHIS}} | ||
{{sc|ML_FF_CSLOPE|Examples|Examples that use this tag}} | {{sc|ML_FF_CSLOPE|Examples|Examples that use this tag}} | ||
Revision as of 07:55, 8 June 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 error is at least twice the slope. We recommend to vary only ML_FF_CSIG and keep ML_FF_CSLOPE fixed to its default value.
Related Tags and Sections
ML_FF_LMLFF, ML_FF_ISAMPLE, ML_FF_LCRITERIA, ML_FF_CSIG, ML_FF_MHIS