0 ×

H2O Partitioning

KNIME H2O Machine Learning Integration version 4.2.0.v202006291607 by KNIME AG, Zurich, Switzerland

The H2O partitioner partitions an H2O frame into two disjoint sets. The size of the set is specified either as an absolute or relative value.
Note: For efficiency reasons resulting partitioning may not be exactly correspond to the selected size or ratio.

Options

Absolute
Specify the absolute number of rows in the first partition. If there are less rows than specified here, all rows are entered into the first table, while the second table contains no rows.
Note: For efficiency reasons resulting partitioning may not be exactly correspond to the selected size or ratio.
Relative[%]
The percentage of the number of rows in the input frame that are in the first partition. It must be between 0 and 100, inclusively.
Note: For efficiency reasons resulting partitioning may not be exactly correspond to the selected size or ratio.
Take from top
This mode puts the top-most rows into the first output table and the remainder in the second table.
Draw randomly
Random sampling of all rows, you may optionally specify a fixed seed (see below).
Stratified sampling
Check this button if you want stratified sampling, i.e. the distribution of values in the selected column is (approximately) retained in the output frames. You may optionally specify a fixed seed (see below).
Use static random seed
If either random or stratified sampling is selected, you may enter a fixed seed here in order to get reproducible results upon re-execution. If you do not specify a seed, a new random seed is taken for each execution.

Input Ports

Icon
H2O frame to partition.

Output Ports

Icon
First H2O frame (as defined in dialog).
Icon
Second H2O frame (remaining rows).

Best Friends (Incoming)

Best Friends (Outgoing)

Workflows

Installation

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

KNIME 4.2

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

You don't know what to do with this link? Read our NodePit Product and Node Installation Guide that explains you in detail how to install nodes to your KNIME Analytics Platform.

Wait a sec! You want to explore and install nodes even faster? We highly recommend our NodePit for KNIME extension for your KNIME Analytics Platform. Browse NodePit from within KNIME, install nodes with just one click and share your workflows with NodePit Space.

Developers

You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.