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

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