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Machine Learning Models

To integrate IFS Cloud with IFS Planning & Scheduling Optimization (PSO) Machine Learning Engine a machine learning model is required.

The machine learning model represents the machine learning features, the mapping between features and IFS Cloud data, and configuration options that will be passed to PSO Machine Learning engine for training.

The machine learning model may consist of Machine Learning and System data.

  • Machine Learning Data: is used to define machine learning features and mapping data between machine learning features and IFS Cloud data tables.
  • System Data: is used for system data integrations.

Read more about Scheduling Optimization and Machine Learning and Scheduling Optimization Business Components for provided integrations

Activities in Machine Learning Models

Enable/Disable Dataset

This command enables or disables the Machine Learning Model.

Train/Re-Train Model

This will send all machine learning and system data to IFS PSO for the selected machine learning model. The machine learning data will be used to train the machine learning model in IFS PSO.

Refresh Model Status

This will query the status of the machine learning model from IFS PSO and display it on the selected Machine Learning Model record.

Edit/View Parameters

This opens a dialog where the dataset parameters can be modified or viewed.

Parameters can only be modified when the dataset is disabled.

Refresh Parameters

This will delete the existing parameters and recreate them from the Machine Learning Model. It will preserve values already entered in the existing parameters.

Parameters can only be refreshed when the dataset is disabled.

PSO Workbench

This command will open the PSO Workbench in a separate window/tab based on the settings defined in Scheduling Optimization and Machine Learning Configuration for the Configuration ID linked to the selected dataset.