Add Principal Component Analysis (PCA) to workflow

  1. In the Stages panel, scroll to Machine Learning, and drag the PCA stage onto the canvas.
  2. Connect the stage to other stages.

    The input stage must be the data source that contains the principal components for your model. An output stage is not required but you may connect one if you wish to capture your output independent of the Machine Learning Model Management tool.

    For more information, see PCA Stage ports.

  3. Double-click the PCA stage to open PCA Properties.
  4. On the Model Properties tab, configure the model name, number of principal components, and the input fields to be included in the analysis.
    For more information about options on this tab, see Model Properties tab.
  5. On the Basic Options tab, configure to use all factor level, to score input data, the transform, and how to handle missing data.
    For more information about options on this tab, see Basic Options tab.
  6. On the Advanced Options tab, configure whether to ignore constant fields, the PCA method, and convergence criteria.
    For more information about options on this tab, see Advanced Options tab
  7. Click Apply to save your changes.