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Titanic
Component Counterfactual Explainable AI Integrated Deployment Iris ML Interpretability SHAP Surrogate Model Wine
  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
    corey
  2. Workflow
    Local Interpretation Workflow
    XAI Counterfactual AutoML
    +7
    This workflow demonstrates the use of the Local Explanation View component on three separate datasets on which the AutoML compone…
    corey > Public > 01_Local_Explanation_Examples
    1
    paolotamag
  3. Workflow
    Model Interpretability: SHAP to explain predictions of Decision Tree
    Titanic ML Interpretability Decision Tree
    +2
    Demonstrates use of SHAP implemenatation in KNIME 4.0 and generates a basic view. Uses Decision Tree model for predicting surviva…
    lisovyi > Public > forum > 18358
    0
    lisovyi
  4. 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
  5. Workflow
    Titanic KNIME Beispiel (deutsch) - einige Graphiken erstellen
    Knime Titanic Graphic
    +2
    Titanic: Machine Learning from Disaster
    mlauber71 > Public > knime_einfuehrung_beispiel_titanic > m_200_digitize_titanic_beispiel
    0
    mlauber71
  6. Workflow
    Local Explanation View Component with AutoML
    XAI Counterfactual AutoML
    +7
    This workflow demonstrates the use of the Local Explanation View component on three separate datasets on which the AutoML compone…
    k10shetty1 > XAI Space > Classification > AutoML > 01_Local_Explanation
    0
    k10shetty1
  7. Workflow
    Daten für Data Mining vorbereiten, Missings behandeln und Aufteilung in Training (70%) und Test (30%) vornehmen
    Titanic Daten Aufbereitung
    +3
    Titanic: Machine Learning from Disaster https://www.kaggle.com/c/titanic Einführung in KNIME (deutsch) - https://hub.knime.com/ml…
    mlauber71 > Public > knime_einfuehrung_beispiel_titanic > m_100_prediction_daten_vorbereiten
    0
    mlauber71
  8. Workflow
    Local Explanation View Component with a Custom Model
    XAI Counterfactual Integrated Deployment
    +10
    This workflow demonstrates the use of the Local Explanation View component on three separate datasets on which the different cust…
    k10shetty1 > XAI Space > Classification > Custom Models > 01_Local_Explanation
    0
    k10shetty1
  9. Workflow
    Titanic - ML Project
    KNIME Titanic Machine Learning
    +1
    This will be the first dataset everyone starts for kaggle competitions. The dataset is easy to interpret and can start with the b…
    augustinejoseph > Public > Titanic - ML Project
    0
    augustinejoseph