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Machine Learning ModelΒΆ

A Machine Learning Model is currently defined as a Scheduling Model. This may change in future releases. To create a Machine Learning Model follow the same process as for creating a Scheduling Model. However, for machine learning models, the supported regions are parameters, systemdata and machinelearningdata.

The following entities must be provided in the machinelearningdata region for a functioning machine learning model.

  • mlmodel - Specify the feature that will be predicted using this model (output feature).
  • mlfeature - List of features and their data types. This should include both input and output features.
  • mlcsv - A SQL query that will provide training data. The columns in this query must match with the feature id's.

Example Machine Learning Model

Once the model is deployed to the database and the Dictionary Cache is refreshed a dataset record can be created for its generated PL/SQL package in Machine Learning Model page in IFS Cloud.

There are Machine Learning Interfaces that allows requesting Model Statistics and making Inference Requests for the machine learning model.