The following node is available in the Open Source KNIME predictive analytics and data mining platform version 2.7.1. Discover over 1000 other nodes, as well as enterprise functionality at http://knime.com.

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.

Dialog Options

Number of validations
The number of cross validation iterations that should be performed.
Random sampling
If checked, the partitions are sampled randomly from the input table, otherwise it is cut into consecutive pieces.
Stratified sampling
If checked, the partitions are sampled randomly but the class distribution from the column selected below is maintained.
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.
Class column name
The name of the column with the class labels.
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.

Ports

Input Ports
0 The datatable that is to be split
Output Ports
0 The data table with the training data
1 The data table with the test data
This node is contained in KNIME Base Nodes provided by KNIME GmbH, Konstanz, Germany.