H2O Local Context

Source

A local H2O context allows to create objects in a locally running H2O instance. For example data tables can be converted to H2O frames and models created using H2O can be applied on those. Note: If run locally, H2O shares compute resources with KNIME Analytics Platform.

Output Ports

  1. Type: H2O Context
    Context for local H2O execution.

  1. H2O scoring model performance metrics

    H2O scoring machine learning model evaluation
    This example shows how to evaluate the performance of H2O classification (binominal and multinominal) and regression mod…
    Users > shima0011 > 04_Analytics > 15_H2O_Machine_Learning

  2. Isolation_Forest_for_Fraud_Detection_Training

    Users > kathrin > Faud_Detection_Autoencoder

  3. 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

  4. 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

  5. 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

  6. H2O Isolation Forest for Outlier Detection

    H2O machine learning Isolation Forest Outlier anomaly detection credit card fraud
    This workflow explains how to train an Isolation Forest model in H2O which can then be used to detect outliers or anomal…
    Users > shima0011 > 04_Analytics > 15_H2O_Machine_Learning

  7. H2O Parameter Optimization

    H2O machine learning parameter optimization grid search
    This workflow shows how to use Parameter Optimization in combination with H2O. In the example we train multiple GBM mode…
    Users > shima0011 > 04_Analytics > 15_H2O_Machine_Learning

  8. Analytics - Model Selection to Predict Flight Departure Delays

    data science machine learning model selection data preparation ETL airline data set
    This workflow trains a number of data analytics models and automatically selects the best model to predict departure del…
    Users > knime > Examples > 50_Applications > 28_Predicting_Departure_Delays

  9. Prediction_h2o_rndfor

    Users > knime > Examples > 50_Applications > 36_Guided_Analytics_for_ML_Automation > 01_Guided_Analytics_for_ML_Automation > Prediction

  10. H2O Generalized Linear Model for regression

    H2O Generalized Linear Model machine learning glm
    This example shows how to build an H2O GLM model for regression, predict new data and score the regression metrics for m…
    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