15_H2O_Machine_Learning
This directory contains 11 workflows.
01_H2O_Data_import_and_export
The H2O Local Context Node starts a single node H2O instance and provides the connection for KNIME. In order to leverage the highspeed algorithms […]
02_H2O_GBM_Classification_Model
This workflow explains how to train a GBM classifier in H2O, predict classes of new data and evaluate the performance. 1. Prepare: Load the IRIS data, […]
03_H2O_GLM_Regression_Model
This example shows how to build an H2O GLM model for regression, predict new data and score the regression metrics for model evaluation. 1. Prepare: Load […]
04_H2O_Crossvalidation
This workflow shows how to use cross-validation in H2O using the KNIME H2O Nodes. In the example we use the H2O Random Forest to predict the multiclass […]
05_H2O_Scoring
In this example we take a look at the KNIME Nodes for H2O Scoring. There are different H2O Scorer Nodes in KNIME for different Machine Learning problems: […]
06_H2O_GBM_parameter_optimization
This tutorial shows how to train multiple H2O Models in KNIME using parameter optimization (grid search) and extract the optimal algorithm settings for the […]
07_Customer_prediction_with_H2O
Customer prediction with H2O in KNIME The purpose of this workflow is to showcase the ease of use of the H2O functionalities from within KNIME. As a real […]
08_H2O_Isolation_Forest_Outlier_Detection
This tutorial shows how to train an H2O Model in KNIME. We will train an Isolation Forest Model to detect frauds, i.e. outliers or anomalies, in a credit […]
09_H2O_DriverlessAI_Example
H2O Driverless AI Integration This workflow shows how to utilize H2O Driverless AI in KNIME to create a model. It starts off with data ingestion and […]
10_H2O_DriverlessAI_CreditCard
KNIME H2O Driverless AI Credit Card This workflow shows how to utilize the new H2O Driverless AI nodes. In order to run the workflow, you will need […]