H2O.ai AutoML (wrapped with Python) with vtreat data preparation in KNIME for classification problems (with R vtreat) - a powerful auto-machine-learning framework (https://hub.knime.com/mlauber71/spaces/Public/latest/automl/)
For details please refer to these entries:
https://forum.knime.com/t/h2o-ai-automl-in-knime-for-classification-problems/20923
This is a modified version that also offers R package vtreat to prepare data and store the preparation and also uses a split of training and test (70/30) while splitting the remaining 70% again (80/20) to get more stable results
External resources
- paolotamag - more options for AutoML with KNIME components
- Cohen's Kappa: what it is, when to use it, how to avoid pitfalls
- Machine Learning Meta Collection (with KNIME)
- Meta Collection about KNIME and Python
- A meta collection and article about R and KNIME
- KNIME Interactive R Statistics Integration Installation Guide
- H2O.ai AutoML in KNIME for classification problems
- R Tip: Use the vtreat Package For Data Preparation
- Combine Big Data, Spark and H2O.ai Sparkling Water
- A Deep dive into H2O’s AutoML
- Profile mlauber71
- KNIME Python Integration Installation Guide
- KNIME, Python and Anaconda - the short story
- Downloading & Installing H2O
Used extensions & nodes
Created with KNIME Analytics Platform version 4.3.1
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