ML MCONF NEW: Difference between revisions
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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. | 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 | {{NB|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: [[Machine learning force field calculations: Basics#Sampling of training data and local reference configurations|here]]. | 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, calculations are usually more efficient, if this parameter is increased. | |||
== Related tags and articles == | == Related tags and articles == | ||
Revision as of 09:24, 29 July 2022
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, calculations are usually more efficient, if this parameter is increased.