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  • From Modeling to Scoring Finding an Optimal Classification based on Cost and Profit
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From Modeling to Scoring: Finding an Optimal Classification based on Cost and Profit

classification model model evaluation profit cost accuracy +1

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This workflow trains a classification model using the Linear Regression algorithm. The class prediction is evaluated by overall accuracy and profit statistics. To calculate the profit statistics, classification results are weighted by the values in a predefined profit matrix. The values in the profit matrix depend on the final goal of the classification model.

External resources

  • From Modeling to Scoring: Finding an Optimal Classification Threshold based on Cost and Profit
  • German Credit Card Data Set provided by University of California Archive for Machine Learning and Intelligent Systems

Used extensions & nodes

Created with KNIME Analytics Platform version 4.3.1
  • KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.1

  • KNIME Expressions Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • KNIME JavaScript Views (Labs) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.1

Legal

By downloading the workflow, you agree to our terms and conditions.

License (CC-BY-4.0)
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