Numeric Scorer

This node computes certain statistics between the a numeric column's values (r _i ) and predicted (p _i ) values. It computes R² =1-SS _res /SS _tot =1-Σ(p _i -r _i )²/Σ(r _i -1/n*Σr _i )² (can be negative!), mean absolute error (1/n*Σ|p _i -r _i |), mean squared error (1/n*Σ(p _i -r _i )²), root mean squared error (sqrt(1/n*Σ(p _i -r _i )²)), and mean signed difference (1/n*Σ(p _i -r _i )). The computed values can be inspected in the node's view and/or further processed using the output table.

Options

Reference column

Column with the correct, observed, training data values.

Predicted column

Column with the modeled, predicted data values.

Change column name

Change the default output column name.

Output column name

The name of the column in the output.

Output scores as flow variables

Activate to receive all scores as flow variables.

Prefix of flow variables

The scores can be exported as flow variables with a hard coded name. This option allows you to define a prefix for these variable identifiers so that name conflicts are resolved.

Views

Statistics

A table with the statistical measures

Workflows

• 01_Guided_AnalyticsKNIME Hub
• 01_Guided_AnalyticsKNIME Hub
• 01_Learning_a_Simple_Regression_TreeKNIME Hub
• 01_Learning_a_Simple_Regression_TreeKNIME Hub
• 01_Learning_a_Simple_Regression_TreeKNIME Hub
• Show all 29 workflows

Links

• Predictive analytics for Salesby mlauber71 on 2018-12-11

  forum.knime.com/p/51276
• Forecasting sales per customer for the next 360 daysby mlauber71 on 2019-01-26

  forum.knime.com/p/53526

Developers