xgboost parameter tuning and handling large datasets

This example demonstrates following: 1. Handling Large datasets in KNIME--Setting Memory Policy 2. Feature Engineering 3. ROC curves 4. XGBoost Tree Ensemble Learner for classification 4. xgboost Parameter tuning using Bayesian Optimization Data is from Kaggle--Santander Customer Transaction Prediction.


This is a companion discussion topic for the original entry at https://kni.me/w/Awriqlgr_oz7Vrtf

The workflow looks helpful to what i’m trying to accomplish. Could you please share the dataset ?

Hi there @ttddhoa -

The data is obtainable from Kaggle here: