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Train suggestion engine to improve quick insert results based on models in a folder


slblocksearchdb.trainfrommodelsindir(folder) improves search results based on the models in folder, recursively.


slblocksearchdb.trainfrommodelsindir(folder,'exclude',exclusions) excludes the specified models from updating the suggestion engine.


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Create the cell array exPath for a folder you want to exclude and a model you want to exclude. To train the suggestion engine, use the cell array in the slblocksearchdb.trainfrommodelsindir command.

exPath = {'MyModels/testmodels' 'MyModels/myvdp.slx'}

The command uses the models in the folder 'MyModels' with the exclusions you specified.

Input Arguments

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Folder whose models to use for training the suggestion engine, specified as an absolute or relative path character vector or string scalar.

Example: 'H:/MyModels/trainingmodels' 'MyModels'

Models to exclude from training the suggestion engine, specified as a cell array of character vectors or a string array. Specify folders or models to exclude as a full or relative path. Model names must include the file extension .slx or .mdl.

Example: {'H:/MyModels/trainingmodels' 'MyModels/trainingmodels2' 'MyModels/myvdp.slx'}

Version History

Introduced in R2018a