This plots shows the Predictive Coefficient of Determination (predictive CoD) of the input parameters. If an input parameter is selected using the Predictive CoD Matrix or the respective dimension selection controls in the Common settings pane, the bar chart plot displays the Predictive CoD of this parameter for all output parameters. The Predictive CoD for the full model with all input parameter is listed in brackets behind the actual Predictive CoD value. Accordingly, if an output parameter is selected, the bar chart plot displays the Predictive CoD's of all parameters for this output parameter. The Predictive CoD of the full model (all input parameter terms) is written in the second title line. The information about the underlying model is written in the plot title.

If the MOP option Testing type is set to value Cross validation, see Coefficient of Prognosis

Common Preferences

The following preference settings are available:

For more details, see Plot Preference Settings.

Plot-Specific Preferences

Filter value lower than [%]:

Sets the value where if the coefficient value is below this number, data is filtered from the chart. The default value of 0.0 means no filtering.

Python scripting

Create Visual

Creates a Predictive Coefficient of Determination plot using data with data_id

    cod = Visuals.CoP(
        Id("Predictive Coefficient of Determination"),
        data_id
    )
                            

Add to Postprocessing

Adds Predictive Coefficient of Determination plot in postprocessing to control_container, using the specified relative positioning.

    control_container.add_control (
        cod,
        True,
        RELATIVE_POSITIONING,
        0, 70/100., 1/2., 30/100.
    )