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¶
- Train Model
- Re-Train Model
- Refresh Model Status
- Edit Parameters
- View Parameters
- Refresh Parameters
- Enable Dataset
- Disable Dataset
- View Background Jobs
- View Application Messages
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.
This opens a dialog where the Dataset parameters can be modified or viewed. Parameters can only be modified when the Dataset is disabled.
This will delete existing parameters and recreate them based on the Machine Learning Package. It will preserve values already entered in the existing parameters.
This RMB option enables or disables the Machine Learning Model.