H2O Gradient Boosting Machine Learner (deprecated)

Learner

Learns a Gradient Boosting Machine (GBM) classification model using H2O .

Input Ports

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

Output Ports

  1. Type: H2O Model
    H2O Gradient Boosting Machine classification model.

  1. 03_Bioactivity_Prediction_Learn_All_Methods

    This workflow is used for learning the model. It deploys a complex parameter optimzation protocol for model building whe…
    Users > knime > Examples > 50_Applications > 37_Monster_Model_Factory > Process > _Process_Step_Templates > workflows > Templates

  2. Model Optimization and Selection

    This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementat…
    Users > shima0011 > 04_Analytics > 11_Optimization

  3. 03_Bioactivity_Prediction_Learn_Testing

    parameter optimization loop machine learning
    This workflow is used for learning the model. It deploys a simple version of parameter optimzation protocol designed for…
    Users > knime > Examples > 50_Applications > 37_Monster_Model_Factory > Process > _Process_Step_Templates > workflows > Templates

  4. Open Source Visualizations and Modeling Integrations

    Open source R Python H2O.ai
    This workflow uses airport and meteorlogical data to predict airline delays. It uses several open source integrations to…
    Users > knime > Examples > 50_Applications > 28_Predicting_Departure_Delays

  5. Model Optimization and Selection

    This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementat…
    Users > knime > Examples > 04_Analytics > 11_Optimization

Extension

This node is part of the extension

KNIME H2O Machine Learning Integration

 v4.0.0

Short Link

Drag node into KNIME Analytics Platform