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This Node Is Deprecated — This node is kept for backwards-compatibility, but the usage in new workflows is no longer recommended. The documentation below might contain more information.

Used in regression tests to test the created data table with a previously stored golden data table. The node will compare (depending on the dialog settings) the incoming tables during execute and fails with an exception if the tables are not equal (or do not meet the expectations). In that case the node stays not executed and the test will fail.

In the node's dialog, select the criteria that should be used to compare the two input tables:


The node succeeds if the two input tables are equal. Each data cell of each row is compared with the corresponding cell of the other table using the DataCell.equalsDataCell() method. For floating point numbers a maximum relative deviation from the reference value can be set, in order to cope with small rounding errors. A value of 0 means that two values must be identical, a value of 1 allows for 100% deviation, i.e. one value may be twice as large as the other.
Fails if an input table is not empty.
A useless and not working option. To be removed soon!
Compares two tables from a Scorer node. Can be used to ensure the classification error of a learner/predictor is within a certain range. The predecessor must be a scorer, the golden table should also be generated by a scorer (probably by the same in a previous run). This option allows specifying the upper and lower tolerance (in percent) for the scorer result. The node succeeds, if the classification error of the current result is not worse than the golden error minus the lower tolerance and not better that the golden classification error plus the upper tolerance.

Input Ports

Datatable with the output of the node to test
The "golden" (i.e. correct) datatable.

Output Ports

This node has no output ports

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