X-Partitioner

This node is the first in a cross validation loop. At the end of the loop there must be a X-Aggregator to collect the results from each iteration. All nodes in between these two node are executed as many times as iterations should be performed.

Options

Number of validations
The number of cross validation iterations that should be performed.
Sampling method
Choose the sampling method for partitioning the data:
  • Linear sampling: The input table is cut into consecutive pieces.
  • Random sampling: The partitions are sampled randomly from the input table.
  • Stratified sampling: The partitions are sampled randomly but the class distribution from the column selected below is maintained.
  • Leave-one-out: Performs a leave-one-out cross validation, i.e. there are as many iterations as data points and in each iteration another point's target value is predicted by using all remaining points as training set.
Class column
The name of the column with the class labels for stratified sampling.
Use random seed
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.
Random seed
The seed value for the random number generator.
Draw seed
Generate a random seed and set it in the Random seed input above for reproducible runs.

Input Ports

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The datatable that is to be split

Output Ports

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The data table with the training data
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The data table with the test data

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Installation

To use this node in KNIME, install the extension KNIME Base nodes from the below update site following our NodePit Product and Node Installation Guide:

v5.9

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

Plugin provider: KNIME AG, Zurich, Switzerland
Plugin version: 5.9.0.v202511140634
On NodePit since: 2025-12-11
Last update: 2025-12-25
Tags: Modern UI
KNIME versions: Since v3.6

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