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Voting Loop End

KNIME Ensemble Learning version 4.3.0.v202011191423 by KNIME AG, Zurich, Switzerland

This node defines the loop end in a sequence of models that are applied to a test dataset. In each iteration the selected prediction column is stored and the most frequent value is determined from this collection of prediction columns. A new column with the name of the selected column containing the majority class of all predictions is appended to the output table. The selected prediction columns are appended (depending on 'Remove individual prediction' option) to the resulting table; all other columns are not part of the output table.


Select the winner column
Column that is used to determine the most frequent value.
Remove individual predictions
Removes all prediction columns generated during the loop iterations; only the final, most frequent prediction is append to the input table.

Input Ports

Table winner column is selected from

Output Ports

Table with all prediction column plus the most frequent value

Best Friends (Incoming)

Best Friends (Outgoing)



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