Conformal Predictor and Classifier (Regression)

The node returns the prediction of conformal regression model based on the regression model and conformal regression calibration table. The purpose of this node is similar to Conformal Predictor. This node is supposed to be used WITH Conformal Calibration and Conformal Prediction loops.


Prediction column
A column with predicted values.
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.
A sensitivity parameter determining the relative importance of the normalization term.
Error rate (significance level)
Defines the tolerable percentage of the prediction errors.
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.

Input Ports

Table with predictions and optionally difficulty estimates from the calibration set.
Table provided by predictor nodes fitted predictions. Target variable must have the same domain as the calibration table.

Output Ports

Table with estimated intervals for predicted values.


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