ML IWEIGHT: Difference between revisions
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The following cases for {{TAG|ML_FF_IWEIGHT}} are possible: | The following cases for {{TAG|ML_FF_IWEIGHT}} are possible: | ||
*{{TAG|ML_FF_IWEIGHT}}=1: Unnormalized energy, force and stress training data are divided by the weights determined by the flags {{TAG|ML_FF_WTOTEN}} (eV/atom), {{TAG|ML_FF_WTIFOR}} ( | *{{TAG|ML_FF_IWEIGHT}}=1: Unnormalized energy, force and stress training data are divided by the weights determined by the flags {{TAG|ML_FF_WTOTEN}} (eV/atom), {{TAG|ML_FF_WTIFOR}} (eV/Angstrom) and {{TAG|ML_FF_WTSIF}} (kBar), respectively. | ||
*{{TAG|ML_FF_IWEIGHT}}=2: The training data are normalized by using their standard deviations. The averaging is done over whole training data. The normalized energy, forces and stress tensor are multiplied by {{TAG|ML_FF_WTOTEN}}, {{TAG|ML_FF_WTIFOR}} and {{TAG|ML_FF_WTSIF}}, respectively. In this case the flags {{TAG|ML_FF_WTOTEN}}, {{TAG|ML_FF_WTIFOR}} and {{TAG|ML_FF_WTSIF}} are unitless quantities. | *{{TAG|ML_FF_IWEIGHT}}=2: The training data are normalized by using their standard deviations. The averaging is done over whole training data. The normalized energy, forces and stress tensor are multiplied by {{TAG|ML_FF_WTOTEN}}, {{TAG|ML_FF_WTIFOR}} and {{TAG|ML_FF_WTSIF}}, respectively. In this case the flags {{TAG|ML_FF_WTOTEN}}, {{TAG|ML_FF_WTIFOR}} and {{TAG|ML_FF_WTSIF}} are unitless quantities. | ||
*{{TAG|ML_FF_IWEIGHT}}=3: Same as {{TAG|ML_FF_IWEIGHT}}=2 but training data is divided into individual systems. The energy, forces and stress tensor for a system are normalized using the average of the standard deviations of each system in the training data. | *{{TAG|ML_FF_IWEIGHT}}=3: Same as {{TAG|ML_FF_IWEIGHT}}=2 but training data is divided into individual systems. The energy, forces and stress tensor for a system are normalized using the average of the standard deviations of each system in the training data. | ||
Revision as of 14:50, 17 May 2019
ML_FF_IWEIGHT = [integer]
Default: ML_FF_IWEIGHT = 3
Description: Flag to control the weighting of training data in the machine learning force field method.
The following cases for ML_FF_IWEIGHT are possible:
- ML_FF_IWEIGHT=1: Unnormalized energy, force and stress training data are divided by the weights determined by the flags ML_FF_WTOTEN (eV/atom), ML_FF_WTIFOR (eV/Angstrom) and ML_FF_WTSIF (kBar), respectively.
- ML_FF_IWEIGHT=2: The training data are normalized by using their standard deviations. The averaging is done over whole training data. The normalized energy, forces and stress tensor are multiplied by ML_FF_WTOTEN, ML_FF_WTIFOR and ML_FF_WTSIF, respectively. In this case the flags ML_FF_WTOTEN, ML_FF_WTIFOR and ML_FF_WTSIF are unitless quantities.
- ML_FF_IWEIGHT=3: Same as ML_FF_IWEIGHT=2 but training data is divided into individual systems. The energy, forces and stress tensor for a system are normalized using the average of the standard deviations of each system in the training data.
Mind: For ML_FF_IWEIGHT=2 and 3 the weights are unitless quantities used to multiply the data, whereas for {TAG|ML_FF_IWEIGHT}}=1 they have a unit and are used to divide the data by them.
Related Tags and Sections
ML_FF_LMLFF, ML_FF_WTOTEN, ML_FF_WTIFOR, ML_FF_WTSIF