NodeH2O 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. Local H2O Context Type: H2O Context
    Context for local H2O execution.
  1. Isolation_Forest_for_Fraud_Detection_Training
    kathrin > Public > Faud_Detection_Autoencoder > Isolation_Forest_for_Fraud_Detection_Training
  2. Model Optimization and Selection
    This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementat…
    knime > Examples > 04_Analytics > 11_Optimization > 08_Model_Optimization_and_Selection
  3. Open Source Visualizations and Modeling Integrations
    Open source R Python H2O.ai Flight delay
    This workflow uses airport and meteorlogical data to predict airline delays. It uses several open source integrations to…
    knime > Examples > 50_Applications > 28_Predicting_Departure_Delays > 03_OpenSourceVizAndModeling
  4. 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…
    knime > Examples > 04_Analytics > 15_H2O_Machine_Learning > 04_H2O_Crossvalidation
  5. 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…
    knime > Examples > 04_Analytics > 15_H2O_Machine_Learning > 06_H2O_GBM_parameter_optimization
  6. 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…
    knime > Examples > 04_Analytics > 15_H2O_Machine_Learning > 05_H2O_Scoring
  7. Compute Local Model-agnostic Explanations (LIMEs)
    LIME machine learning interpretability mli explanation instance-level explanation reason code explain interpret model machine learning XGB XGBoost
    This is an example for computing explanation using LIME. An XGBoost model was picked, but any model and its set of Learn…
    knime > Examples > 04_Analytics > 17_Machine_Learning_Interpretability > 01_Compute_LIMEs
  8. Prediction_h2o_naive
    knime > Examples > 50_Applications > 36_Guided_Analytics_for_ML_Automation > 01_Guided_Analytics_for_ML_Automation > Prediction > Prediction_h2o_naive
  9. h2o_glm
    knime > Examples > 50_Applications > 36_Guided_Analytics_for_ML_Automation > 01_Guided_Analytics_for_ML_Automation > Models > classification > h2o_glm
  10. Prediction_svm
    knime > Examples > 50_Applications > 36_Guided_Analytics_for_ML_Automation > 01_Guided_Analytics_for_ML_Automation > Prediction > Prediction_svm