H2O k-Means

Build and apply a K-Means model using H2O.

Options

Number of clusters: Specify the number of clusters (k).
Maximum number of iterations: Specify the number of training iterations (max_iterations).
Column selection: Select columns used for model training.
Ignore constant columns: Select to ignore constant columns.

Estimate number of clusters: Specify whether to estimate the number of clusters (<=k) iteratively (independent of the seed) and deterministically (beginning with k=1,2,3...) (estimate_k).
Initialization mode: Specify the initialization mode. If mode "User" is selected, user-specified initial cluster centers should be given in the second in-port (init).
Standardize numeric columns: Specify whether to standardize the numeric columns to have a mean of zero and unit variance (recommended) (standardize).
Select categorical encoding: Specify one of the following encoding schemes for handling categorical features (categorical_encoding).

Max runtime in seconds: Maximum allowed runtime in seconds for model training (max_runtime_secs).
Use static random seed: Select to use static seed for randomization.

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To use this node in KNIME, install the extension KNIME H2O Machine Learning Integration from the below update site following our NodePit Product and Node Installation Guide:

v5.3

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

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.3.0.v202312081534

On NodePit since: 2024-07-09

Last update: 2024-11-15

KNIME versions: Since v3.7

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