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  • 01_Evaluating_Classification_Model_Performance
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Evaluating Classification Model Performance

Classification model Model evaluation Confusion matrix Class prediction statistics Accuracy
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This workflow trains a classification model using the Decision Tree algorithm and evaluates its accuracy by scoring metrics, ROC Curve, and Lift Chart.

External resources

  • Spambase Data Set provided by UCI Machine Learning Repository
  • German Credit Card Data Set provided by UCI Machine Learning Repository
  • ROC Curve of a Classification Model
  • What is an ROC Curve?
  • Evaluating Classification Model Performance with the Scorer (JavaScript) Node
  • From Modeling to Scoring: Confusion Matrix and Class Statistics

Used extensions & nodes

Created with KNIME Analytics Platform version 4.4.0
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    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.0

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    KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.0

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    KNIME JavaScript Views (Labs) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.0

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    KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.0

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