H2O Random Forest Learner

Learner

Learns a Distributed Random Forest (DRF) classification model using H2O .

Input Ports

  1. Type: H2O Frame
    H2O Frame with training data.

Output Ports

  1. Type: Data
    Variable importance in tabular format.
  2. Type: H2O Model
    H2O Distributed Random Forest classification model.

  1. H2O Cross-Validation

    H2O machine learning cross-validation
    This workflow shows how to use cross-validation in H2O using the KNIME H2O Nodes. In the example we use the H2O Random F…
    Users > shima0011 > 04_Analytics > 15_H2O_Machine_Learning

  2. H2O Cross-Validation

    H2O machine learning cross-validation
    This workflow shows how to use cross-validation in H2O using the KNIME H2O Nodes. In the example we use the H2O Random F…
    Users > knime > Examples > 04_Analytics > 15_H2O_Machine_Learning

Extension

This node is part of the extension

KNIME H2O Machine Learning Integration

 v4.0.0

Short Link

Drag node into KNIME Analytics Platform