ML CSLOPE: Difference between revisions

Revision as of 17:20, 21 October 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.

The usage of this tag in combination with the learning algorithms is described here: here.

@@ Line 3: / Line 3: @@
 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_ICRITERIA}} 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.
+The usage of this tag in combination with the learning algorithms is described here: [[Machine learning force field calculations: Important algorithms#Threshold for error of forces|here]].
 == Related Tags and Sections ==
-{{TAG|ML_LMLFF}}, {{TAG|ML_ICRITERIA}}, {{TAG|ML_CSIG}}, {{TAG|ML_MHIS}}
+{{TAG|ML_LMLFF}}, {{TAG|ML_ICRITERIA}}, {{TAG|ML_CSIG}}, {{TAG|ML_MHIS}}, {{TAG|ML_CX}}
 {{sc|ML_CSLOPE|Examples|Examples that use this tag}}