Interpretability of Classification models

Workflow

Interpretability of Classification models

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This workflow demontstrates the usage of XAI techniques, global and local explanations for intrepreting the decision making of the classification of the models . This workflow is also a solution to the Just KNIME It challenge 26

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Interpretability of Classification models

KNIME Base nodes

KNIME Data Generation

KNIME Deep Learning - Keras Integration

KNIME Ensemble Learning Wrappers

KNIME H2O Machine Learning Integration

KNIME Integrated Deployment

KNIME JavaScript Views

KNIME Javasnippet

KNIME Machine Learning Interpretability Extension

KNIME Math Expression (JEP)

KNIME Optimization extension

KNIME PMML Preprocessing Applier Nodes

KNIME Quick Forms

KNIME XGBoost Integration

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Interpretability of Classification models

Used extensions & nodes

KNIME Base nodesTrusted extension

KNIME Data GenerationTrusted extension

KNIME Deep Learning - Keras IntegrationTrusted extension

KNIME Ensemble Learning WrappersTrusted extension

KNIME H2O Machine Learning IntegrationTrusted extension

KNIME Integrated DeploymentTrusted extension

KNIME JavaScript ViewsTrusted extension

KNIME JavasnippetTrusted extension

KNIME Machine Learning Interpretability ExtensionTrusted extension

KNIME Math Expression (JEP)Trusted extension

KNIME Optimization extensionTrusted extension

KNIME PMML Preprocessing Applier NodesTrusted extension

KNIME Quick FormsTrusted extension

KNIME XGBoost IntegrationTrusted extension

Legal

KNIME Base nodes

KNIME Data Generation

KNIME Deep Learning - Keras Integration

KNIME Ensemble Learning Wrappers

KNIME H2O Machine Learning Integration

KNIME Integrated Deployment

KNIME JavaScript Views

KNIME Javasnippet

KNIME Machine Learning Interpretability Extension

KNIME Math Expression (JEP)

KNIME Optimization extension

KNIME PMML Preprocessing Applier Nodes

KNIME Quick Forms

KNIME XGBoost Integration