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Binary Classification - use Python XGBoost package and other nodes to build model and deploy that thru KNIME Python nodes

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Jul 15, 2024 4:20 PM
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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

  • Medium: KNIME — Machine Learning and Artificial Intelligence — A Collection
  • KNIME Hub: a version 5.x instance of this workflow
  • HUB: Binary Classification - use Python XGBoost package and other nodes to build model and deploy that thru KNIME Python nodes
  • H2O.ai AutoML (wrapped with Python) in KNIME for classification problems
  • Medium: Data preparation for Machine Learning with KNIME and the Python “vtreat” package
  • Meta Collection about KNIME and Python
  • forum entry (45057)
  • XGBoost Parameters
  • A Beginner’s guide to XGBoost
  • How to Develop Your First XGBoost Model in Python
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Used extensions & nodes

Created with KNIME Analytics Platform version 4.7.8
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