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01 Analyze Data by Training a Decision Tree

BeginnerBeginner SpaceGetting StartedData AnalysisMachine Learning
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Versionv2.0Latest, created on 
May 11, 2026 3:44 PM
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Analyze Data: Training a Decision Tree

This workflow is an example of how to train and evaluate a basic machine learning model for a churn prediction task.

In this case, we train and apply a Decision Tree algorithm, however, the Learner-Predictor construct is common to all supervised algorithms.

External resources

  • KNIME Learning Center
  • KNIME Cheat Sheet: Building a KNIME workflow for beginners
  • KNIME Cheat Sheet: Machine learning with KNIME Analytics Platform
  • YouTube: Training and Applying Decision Trees in KNIME
  • YouTube: Behind the Scenes of the Decision Tree with KNIME
  • KNIME Blog: Predict Customer Churn with a Low-Code ML Solution
  • Webinar: KNIME101: Machine Learning for Beginners with KNIME
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Created with KNIME Analytics Platform version 5.11.0
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    KNIME Base nodesTrusted extension

    KNIME AG, Zurich, Switzerland

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    KNIME Excel SupportTrusted extension

    KNIME AG, Zurich, Switzerland

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    KNIME ViewsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.11.0

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