Specifying a repository for Prediction Studio models
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Enable creating and storing machine-learning models in your application by specifying a resilient repository for model training and historical data.
If your application contains complete machine-learning models, minimize the risk of data loss by saving a copy of the models in your local directory. For more information, see Exporting text analytics models.
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In the navigation pane of Prediction Studio, click .
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In the Storage section, in the Analytics repository field, press the Down arrow key, and then select a repository for the model data.
Select a resilient repository, for example, an Amazon Web Services repository. To avoid data loss, do not use thedefaultstorerepository that is located under/tomcat/Work/Catalina/localhost/prweb/.The model data is stored in the repository that you specified, in thenlpcontents/modelsfolder. For example,nlpcontents/models/@baseclass/NLPSample/01-01-06/Int_1/trainingdata, where:- @baseclass is the class name.
- NLPSample is the ruleset.
- 01-01-06 is the ruleset version.
- Int_1 is the model name.
- trainingdata is the name of the folder that contains the training data for text analytics models.
- Optional:
To include training data when you export text analytics models, perform one of the following actions:
- To migrate text analytics models to production systems, clear the Include historical data source in text model export check box.
- To migrate text analytics models to non-production systems, select the Include historical data source in text model export check box.
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In the Confirm repository change dialog box, click Submit.
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Click Save.
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If you saved a copy of the text analytics models in your application as described in the Before you begin section, upload the models to Prediction Studio.
For more information, see Importing text analytics models.
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Effortlessly analyze and extract meaningful information from large volumes of text with the use of text analytics. Based on your findings, you can further improve business performance and customer experience.