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01_​Classify_​Forest_​Covertypes_​with_​XGBoost

Forest Cover Type Classification with XGBoost

This workflows shows how the XGBoost nodes can be used for classification tasks.

Forest Cover Type Classification with XGBoostThis workflows shows how the XGBoost nodes can be used for classification tasks.The data can be found at https://archive.ics.uci.edu/ml/datasets/covertype.Workflow RequirementsKNIME Analytics Platform 3.7.0 or higherKNIME XGBoost Integration The model accuracyshould be roughly 86% train / test80 / 20train model ontraining datapredict test datascore prediction Partitioning Read andPreprocess Data XGBoost TreeEnsemble Learner XGBoost Predictor Scorer Forest Cover Type Classification with XGBoostThis workflows shows how the XGBoost nodes can be used for classification tasks.The data can be found at https://archive.ics.uci.edu/ml/datasets/covertype.Workflow RequirementsKNIME Analytics Platform 3.7.0 or higherKNIME XGBoost Integration The model accuracyshould be roughly 86% train / test80 / 20train model ontraining datapredict test datascore predictionPartitioning Read andPreprocess Data XGBoost TreeEnsemble Learner XGBoost Predictor Scorer

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: Adrian Nembach
Created at: 2018-12-04
On NodePit since: 2019-07-12
Last update: 2024-04-18
Created with KNIME version: v4.1.0
Tags: XGBoost classification gradient boosting gradient boosted trees parameter optimization cross validation data mining advanced analytics analytics machine learning

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