ML MCONF NEW: Difference between revisions

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{{TAGDEF|ML_FF_MCONF_NEW|[integer]|5}}
{{DISPLAYTITLE:ML_MCONF_NEW}}
{{TAGDEF|ML_MCONF_NEW|[integer]|5}}


Description:
Description: This tag sets the number of configurations that are stored temporarily as candidates for the training data in the machine learning force field method.
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{{NB|warning|This value is close to optimal for on-the-fly learning,  and should usually not be changed. }}


== Related Tags and Sections ==
The use of this tag in combination with the learning algorithms is described here: [[Machine learning force field calculations: Basics#Sampling of training data and local reference configurations|here]].
If force fields are reparameterized ({{TAGO|ML_MODE|select}}), calculations are usually more efficient if this parameter is increased to values around 10-16 and setting {{TAGO|ML_CDOUB|4}}. This is particularly relevant if the ML_AB file is large.


{{sc|ML_FF_MCONF_NEW|Examples|Examples that use this tag}}
== Related tags and articles ==
 
{{sc|ML_MCONF_NEW|Examples|Examples that use this tag}}
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{{TAG|ML_LMLFF}}, {{TAG|ML_MCONF}}, {{TAG|ML_CTIFOR}}, {{TAG|ML_CDOUB}}


[[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]]
[[Category:INCAR tag]][[Category:Machine-learned force fields]]

Latest revision as of 15:32, 19 October 2023

ML_MCONF_NEW = [integer]
Default: ML_MCONF_NEW = 5 

Description: This tag sets the number of configurations that are stored temporarily as candidates for the training data in the machine learning force field method.


Warning: This value is close to optimal for on-the-fly learning, and should usually not be changed.

The use of this tag in combination with the learning algorithms is described here: here. If force fields are reparameterized (ML_MODE = select), calculations are usually more efficient if this parameter is increased to values around 10-16 and setting ML_CDOUB = 4. This is particularly relevant if the ML_AB file is large.

Related tags and articles

Examples that use this tag


ML_LMLFF, ML_MCONF, ML_CTIFOR, ML_CDOUB