Binary Classification - use Python XGBoost package and other nodes to build model and deploy that thru KNIME Python nodes
prepare data with vtreat package
in the subfolder /data/ there is a Jupyter notebook to experiment and build XGBoost models ("kn_example_python_xgboost.ipynb")
Dataset: Census Income Data Set
Abstract: Predict whether income exceeds $50K/yr based on census data. Also known as "Adult" dataset.
https://archive.ics.uci.edu/ml/datasets/census+income
External resources
- How to Develop Your First XGBoost Model in Python
- A Beginner’s guide to XGBoost
- XGBoost Parameters
- forum entry (45057)
- Meta Collection about KNIME and Python
- Medium: Data preparation for Machine Learning with KNIME and the Python “vtreat” package
- H2O.ai AutoML (wrapped with Python) in KNIME for classification problems
- HUB: Binary Classification - use Python XGBoost package and other nodes to build model and deploy that thru KNIME Python nodes
Used extensions & nodes
Created with KNIME Analytics Platform version 4.7.8
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KNIME H2O Machine Learning Integration - MOJO Extension
KNIME AG, Zurich, Switzerland
Version 4.7.0
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