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Binary Classification Inspector Example

binary classification machine learning model Bayesian RandomForest XGBoost Tree

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This workflow demonstrates the functionality of the Binary Classification Inspector node. It produces a complex view made of four different charts in order to compare, optimize and select predictions of different binary classifiers. It is possible to compare a number of binary classifier machine learning models predicting the same target on the same test data using performance metrics and ROC curves. Here three machine learning models are used: Bayesian, RandomForest, and XGBoost Tree. By moving a threshold slider in the interactive view you can optimize a model by finding the best threshold given a performance metric of your choice. It is possible to interactively select a given type of predictions (e.g. true positives) of one of the models and export them at the output of the node

Used extensions & nodes

Created with KNIME Analytics Platform version 4.1.0
  • KNIME Base Chemistry Types & Nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • KNIME Core Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • KNIME Machine Learning Interpretability Extension Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • KNIME XGBoost Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • RDKit KNIME integration Trusted extension

    NIBR

    Version 4.0.0

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License (CC-BY-4.0)
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