ML CX: Difference between revisions
No edit summary |
No edit summary |
||
| Line 13: | Line 13: | ||
== Related Tags and Sections == | == Related Tags and Sections == | ||
{{TAG|ML_LMLFF}}, {{TAG|ML_ICRITERIA}}, {{TAG|ML_CTIFOR}}, {{TAG|ML_MHIS}} | {{TAG|ML_LMLFF}}, {{TAG|ML_ICRITERIA}}, {{TAG|ML_CTIFOR}}, {{TAG|ML_MHIS}}, {{TAG|ML_CSIG}}, {{TAG|ML_CSLOPE}} | ||
{{sc|ML_LCRITERIA|Examples|Examples that use this tag}} | {{sc|ML_LCRITERIA|Examples|Examples that use this tag}} | ||
Revision as of 17:18, 21 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.
The usage of this tag in combination with the learning algorithms is described here: here.
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, ML_CSIG, ML_CSLOPE