reuse_points

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• Keywords Area
• model
• surrogate
• global
• reuse_points

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Surrogate model training data reuse control

Topics

This keyword is related to the topics:

• surrogate_models

Specification

Alias: reuse_samples

Argument(s): none

Default: all for import; none otherwise

	Required/Optional	Description of Group	Dakota Keyword	Dakota Keyword Description
	Required (Choose One)	Group 1	all	Option for reuse_points
			region	Option for reuse_points
			none	Option for reuse_points

Description

Dakota's global surrogate methods rely on training data, which can either come from evaluation of a "truth" model, which is generated by the method specified with dace_method_pointer, from a file of existing training data, identified by import_points_file, or both.

The reuse_points keyword controls the amount of training data used in building a surrogate model, either initially, or during iterative rebuild, as in surrogate-based optimization. If import_points_file is specified, reuse_points controls how the file contents are used. If used during iterative rebuild, it controls what data from previous surrogate builds is reused in building the current model.

• all (default for file import) - use all points in the file or available from previous builds
• region - use only the points falling in the current trust region (see surrogate_based_local)
• none (default when no import) - ignore the contents of the file or previous build points, and gather new training data using the specified DACE method