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Interpretability
Guided analytics Global feature importance Global surrogate models Integrated deployment Machine learning Permutation feature importance Surrogate GLM Surrogate decision tree Surrogate random forest
  1. Workflow
    Model Interpretability, Titanic
    Titanic Random Forest ML Interpretability
    +6
    The workflow demonstrates how to use SHAP, Shapley Values and LIME implemenatations in KNIME 4.0 and generates a basic combined v…
    knime > Examples > 04_Analytics > 17_Machine_Learning_Interpretability > 03_Titantic_Prediction_Explanations
    4
    knime
  2. Workflow
    Compute and Visualize Global Feature Importance Metrics
    AutoML Automated machine learning Guided analytics
    +9
    This application is a simple example of inspecting global feature importance for binary and multiclass classification with KNIME …
    lada > Public > XAI > 01_Global_Feature_Importance_Example
    1
    lada
  3. Workflow
    Guided Analytics with Shared Components - Preview
    Guided analytics Shared component AutoML
    +13
    --------------- !!! DISCLAIMER !!! --------------- These Components are not-verified Beta versions shared in Fall 2019 on my pers…
    paolotamag > Public > Guided_Analytics_with_Shared_Components
    1
    paolotamag
  4. Workflow
    Global Feature Importance Component with a Custom Model
    Guided analytics Integrated deployment Interpretability
    +7
    This application is a simple example of inspecting global feature importance for binary and multiclass classification with KNIME …
    knime > XAI Space > Classification > Custom Models > 03_Global_Feature_Importance
    0
    knime
  5. Workflow
    Interpretability of Classification models
    Justknimeit Justknimeit-26 Interpretability
    +2
    This workflow demontstrates the usage of XAI techniques, global and local explanations for intrepreting the decision making of th…
    mpattadkal > Public > Just_KNIME_It > Challenge_26
    0
    mpattadkal
  6. Workflow
    Compute and Visualize Global Feature Importance for a Custom Model
    Guided analytics Integrated deployment Interpretability
    +7
    This application is a simple example of inspecting global feature importance for binary and multiclass classification with KNIME …
    lada > Public > XAI > 06_Global_Feature_Importance_for_a_Custom_Model
    0
    lada
  7. Workflow
    Model Interpretability, Titanic
    Titanic Random Forest ML Interpretability
    +6
    The workflow demonstrates how to use SHAP, Shapley Values and LIME implemenatations in KNIME 4.0 and generates a basic combined v…
    joelbec > Public > 03_Titantic_Prediction_Explanations
    0
    joelbec
  8. Workflow
    Interactive MLI Composite View
    Machine learning interpretability MLI PDP
    +14
    This worflow will show how to use the interactive views of JavaScript nodes to visualize in a single Composite View a number of M…
    knime > Examples > 04_Analytics > 17_Machine_Learning_Interpretability > 05_Interactive_MLI_Composite_View
    0
    knime