Visualize - Plot input features against output features

MI Machine Learning also allows you to explore a trained model’s parameter space graphically. In this exercise, we’ll view the model’s predictions on a 2D plot.

  1. Click Plot model features.
    This takes you to the Plot Features page, keeping the current model selected.
  2. Click Visualize to plot the default Input and Output with the rest of the input features set to a fixed value.

    The model’s prediction (blue line) and uncertainty (green shaded area) for the selected Output are plotted against the selected Input.

    There are some step changes on the plot. This is expected, particularly for smaller datasets, and is usually due to differences in the training dataset across different parts of the parameter space (for example, having fewer data points or noisier test data in some parts of the model range).

  3. Inspect other parts of the model’s parameter space.
    1. Change the Output (y-axis) to the model’s second output feature, and click Visualize to update the plot.
    2. Edit the fixed Value of the other input features:

      1. In the table, click the Value cell for the inputs you want to edit, and enter the new values.

        The currently-selected Input’s row is grayed out and cannot be edited.

      2. Use the Model range and Correlation to inform your choice of Value.
      3. Click Visualize to re-plot at the new input values.
    3. Click Reset to clear the plot area and restore the default values for Input, Output and the Value column.