Defining Model Properties
-
Under Primary Stages / Deployed
Stages / Machine Learning, click the
PCA Options stage and drag it onto the canvas, placing it
where you want on the dataflow and connecting it to other stages. Note that 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.
-
Double-click the PCA Options stage to show the PCA Options
dialog box.
-
Enter a Model name if you do not want to use the default
name.
-
Optional: Check the Overwrite box to overwrite the
existing model with new data.
-
Enter the number of Principal components you want your
model to contain.
-
Optional: Enter a Description of the model.
-
In the Inputs table click "Include" for each field whose data you want
added to the model.
-
Use the Model Data Type drop-down to specify whether the
input field is to be used as a categorical, datetime, numeric, string, or
uniqueid field.
-
Click OK to save the model and configuration or continue
to the next tab.