ML CX: Difference between revisions
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{{TAGDEF| | {{TAGDEF|ML_CX|[integer]|0.0}} | ||
Description: The parameter determines how the threshold ({{TAG|ML_CTIFOR}}) is updated within the machine learning force field methods. | Description: The parameter determines how the threshold ({{TAG|ML_CTIFOR}}) is updated within the machine learning force field methods. | ||
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{{TAG|ML_CTIFOR}} is set to the average of the Bayesian errors of the forces stored in history (see {{TAG|ML_ICRITERIA}}). The number of entries in the history are controlled by {{TAG|ML_MHIS}}. | {{TAG|ML_CTIFOR}} is set to the average of the Bayesian errors of the forces stored in history (see {{TAG|ML_ICRITERIA}}). The number of entries in the history are controlled by {{TAG|ML_MHIS}}. | ||
{{TAG|ML_CTIFOR}} = (average of the stored Bayesian errors) *(1.0 + {{TAG| | {{TAG|ML_CTIFOR}} = (average of the stored Bayesian errors) *(1.0 + {{TAG|ML_CX}}). | ||
This implies that for {{TAG| | This implies that for {{TAG|ML_CX}}=0, the old value stored in {{TAG|ML_CTIFOR}} is simply overwritten by the current average Bayesian error. | ||
== Related Tags and Sections == | == Related Tags and Sections == | ||
Revision as of 08:12, 13 October 2021
ML_CX = [integer]
Default: ML_CX = 0.0
Description: The parameter determines how the threshold (ML_CTIFOR) is updated within the machine learning force field methods.
If ML_ICRITERIA>0, ML_CTIFOR is set to the average of the Bayesian errors of the forces stored in history (see ML_ICRITERIA). The number of entries in the history are controlled by ML_MHIS.
ML_CTIFOR = (average of the stored Bayesian errors) *(1.0 + ML_CX).
This implies that for ML_CX=0, the old value stored in ML_CTIFOR is simply overwritten by the current average Bayesian error.
Related Tags and Sections
ML_LMLFF, ML_ICRITERIA, ML_CTIFOR, ML_MHIS