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H2O Cross Validation Loop Start

DeprecatedKNIME H2O Machine Learning Integration version 4.4.0.v202106081612 by KNIME AG, Zurich, Switzerland

This node is the first in a cross validation loop. At the end of the loop there can be an arbitrary other loop, for example to collect scoring results. All nodes in between these two node are executed as many times as iterations should be performed.


Number of folds
The number of cross validation iterations that should be performed (nfolds) .
If checked, the partitions are based on row-index%folds. Suitable for i.i.d. data.
If checked, the partitions are sampled randomly but the class distribution from the column selected below is maintained.
If checked, the partitions are sampled randomly from the input table, otherwise it is cut into consecutive pieces.
Class column name
The name of the column with the class labels for stratified sampling.
For random and stratified sampling you can choose a seed for the random number generator in order to get reproducible results. Otherwise you get different partitions every time.

Input Ports

H2O frame that is be used during cross validation.

Output Ports

H2O frame with the training data
H2O frame with the test data

Best Friends (Incoming)

Best Friends (Outgoing)


To use this node in KNIME, install KNIME H2O Machine Learning Integration from the following update site:


A zipped version of the software site can be downloaded here.

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