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)), Mean signed difference (1/n*Σ(p_i-r_i)), Mean absolute percentage error 1/n * Σ((|r_i - p_i|)/ |r_i|), Adjusted R²=1-(1-R²)(n-1)/(n-p-1) (can be negative!). 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.

Override output column name

Overrides the name of the column in the output. By default, the name of the predicted column is used.

Output column name

The name of the column in the output.

Export and prefix flow variables

If enabled, the scores will be exported as flow variables with hard coded names and prefixed by the given value.

Number of predictors

The number of predictors used to compute the adjusted R squared. The adjusted R squared is calculated as: 1 - ((1 - R²) * (n - 1)) / (n - p - 1), where n is the number of observations and p is the number of predictors.

Views

Statistics

A table with the statistical measures

Workflows

• [ISPRENL S11] Group 5 MCO2 WorkflowKNIME Hub
• 001_TS_predikce_SARIMA_basicKNIME Hub
• 01_Accessing_Transforming_and_Modeling_Time_SeriesKNIME Hub
• 01_Accessing_Transforming_and_Modeling_Time_SeriesKNIME Hub
• 01_Accessing_Transforming_and_Modeling_Time_SeriesKNIME Forum
• Show all 1573 workflows

Links

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Developers