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.

Linear sampling

If checked, the input table is cut into consecutive pieces.

Random sampling

If checked, the partitions are sampled randomly from the input table.

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.

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Workflows

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