Predictive Systems Calibrator (Regression)

Creates a calibration table with ranking for further calibration of the test data sets. Ranking is a sorting by absolute error (Alpha) provided by predictor nodes in descending order. In order to use normalization Prediction Variance or estimate of difficulty - Sigma (needs to be calculated separately) should be provided. Alpha values are used for further cumulative distribution function (CDF) calculation. This node is supposed to be used WITH Conformal Calibration and Conformal Prediction loops.

Options

Target column

A column with target column that is being predicted.

Use normalization

in order to increase the informativeness, and to potentially minimize prediction regions, it is possible to obtain individual bounds for each sample, which is achieved using a normalized nonconformity function. In order to use normalization Prediction Variance or estimate of difficulty - Sigma (needs to be calculated separately) should be provided.

Difficulty column

The column that contains the values defining the Sigma. By default it is advisable to use Prediction Variance values.

Beta

A sensitivity parameter determining the relative importance of the normalization term.

Keep All Columns

If checked all columns from input table will be also included into output table along with calibration columns.

Keep ID column

If checked selected ID column from input table will be included into output table.

Views

This node has no views

Workflows

• Conformal predictive systems (advanced)KNIME Hub

Links

• No links available

Developers