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Machine learning interpretability XAI Partial dependence AutoML Integrated deployment Explanation Individual conditional expectation
  1. Workflow
    eXplainable Artificial Intelligence (XAI) - Simple
    AutoML Automated machine learning Guided analytics
    +8
    This application is a simple example of AutoML with KNIME Software for binary and multiclass classification. The output models ar…
    knime > Examples > 09_Enterprise > 04_Integrated_Deployment > 05_Explainable_Artificial_Intelligence_(XAI) > 01_Explainable_Artificial_Intelligence_(XAI)_Simple
    2
    knime
  2. Workflow
    Model Inspection with Verified Components for Responsible AI
    AutoML Integrated deployment XAI
    +9
    This workflow demonstrates the usage of the verified components developed to interpret machine learning models. In the example we…
    paolotamag > Public > Model_Inspection_Examples
    2
    paolotamag
  3. Workflow
    Partial Dependence Plot Example
    Partial dependence Pdp Pdp plot
    +13
    This is an example for visualizing a partial dependence plot and an ICE curves plot in KNIME. An XGBoost model was picked, but an…
    knime > Examples > 04_Analytics > 17_Machine_Learning_Interpretability > 02_Partial_Dependence_Pre-processing
    2
    paolotamag
  4. Workflow
    SHAP and Shapley Values Loop Nodes with AutoML
    Machine learning interpretability Mli Force plot
    +5
    This worflow shows how to use SHAP and Shapley Values Loop nodes and it creates Stacked Bar Charts similar to Force Plots for you…
    k10shetty1 > XAI Space > Classification > AutoML > 06_SHAP_and_Shapley_Values
    1
    k10shetty1
  5. Workflow
    Compute Local Model-agnostic Explanations (LIMEs)
    LIME Machine learning interpretability Mli
    +9
    This is an example for computing explanation using LIME. An XGBoost model was picked, but any model and its set of Learner and Pr…
    knime > Examples > 04_Analytics > 17_Machine_Learning_Interpretability > 01_Compute_LIMEs
    1
    paolotamag
  6. 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
  7. Workflow
    SHAP and Shapley Values Loop Nodes with AutoML (Regression)
    Machine learning interpretability Mli Force plot
    +5
    This worflow shows how to use SHAP and Shapley Values Loop nodes and it creates Stacked Bar Charts similar to Force Plots for you…
    k10shetty1 > XAI Space > Regression > AutoML > 02_SHAP_and_Shapley_Values
    0
    k10shetty1
  8. Workflow
    LIME Loop Nodes with a Custom Model
    LIME Machine learning interpretability Mli
    +9
    This is an example for computing explanation using LIME. An XGBoost model was picked, but any model and its set of Learner and Pr…
    k10shetty1 > XAI Space > Classification > Custom Models > 07_Compute_LIMEs
    0
    k10shetty1
  9. Workflow
    SHAP and Shapley Values Loop Nodes with a Custom Model
    Machine learning interpretability Mli Force plot
    +4
    This worflow shows how to use SHAP and Shapley Values Loop nodes and it creates Stacked Bar Charts similar to Force Plots for you…
    k10shetty1 > XAI Space > Classification > Custom Models > 06_SHAP_and_Shapley_Values
    0
    k10shetty1
  10. Workflow
    Partial Dependence Plot Example
    Partial dependence Pdp Pdp plot
    +13
    This is an example for visualizing a partial dependence plot and an ICE curves plot in KNIME. An XGBoost model was picked, but an…
    keith_mccormick > Public > 02_Partial_Dependence_Pre-processing
    0
    keith_mccormick
  11. Workflow
    SHAP and Shapley Values Loop Nodes with a Custom Regression Model
    Machine learning interpretability Mli Force plot
    +4
    This worflow shows how to use SHAP and Shapley Values Loop nodes and it creates Stacked Bar Charts similar to Force Plots for you…
    k10shetty1 > XAI Space > Regression > Custom Models > 02_SHAP_and_Shapley_Values
    0
    k10shetty1
  12. Workflow
    Partial Dependence Plot with AutoML (Regression)
    Partial dependence Pdp Pdp plot
    +16
    This is an example for visualizing a partial dependence plot and an ICE curves plot in KNIME. AutoML (Regression) Component was u…
    k10shetty1 > XAI Space > Regression > AutoML > 04_Partial_Dependence_Pre-processing
    0
    k10shetty1
  13. Workflow
    LIME Loop Nodes with AutoML
    LIME Machine learning interpretability Mli
    +9
    This is an example for computing explanation using LIME. AutoML component was used to pick the best model, but any model and its …
    k10shetty1 > XAI Space > Classification > AutoML > 07_Compute_LIMEs
    0
    k10shetty1
  14. Workflow
    Finding Counterfactual Explanations and Local Feature Importance for a Selected Prediction of a Credit Scoring Model
    AutoML Integrated deployment XAI
    +8
    In the example, the Credit Scoring data set is partitioned to training and test samples. Then, the black box model (Neural Networ…
    lada > Public > XAI > 04_XAI_Credit_Scoring_Example_Local_Explanation_View
    0
    lada
  15. Workflow
    Partial Dependence Plot with a Custom Regression Model
    Partial dependence Pdp Pdp plot
    +16
    This is an example for visualizing a partial dependence plot and an ICE curves plot in KNIME. An XGBoost Tree Ensemble Regression…
    k10shetty1 > XAI Space > Regression > Custom Models > 04_Partial_Dependence_Pre-processing
    0
    k10shetty1
  16. Workflow
    LIME Loop Nodes with a Custom Regression Model
    LIME Machine learning interpretability Mli
    +10
    An XGBoost Tree Ensemble Regression model was picked, but any model and its set of Learner and Predictor nodes can be used. - Rea…
    k10shetty1 > XAI Space > Regression > Custom Models > 03_Compute_LIMEs
    0
    k10shetty1
  17. Workflow
    Global Feature Importance Component with AutoML
    AutoML Integrated deployment XAI
    +6
    In the example, the Credit Scoring data set is partitioned to training and test samples. Then, the black box model (Neural Networ…
    k10shetty1 > XAI Space > Classification > AutoML > 03_Global_Feature_Importance
    0
    k10shetty1
  18. Workflow
    Compute Local Model-agnostic Explanations (LIMEs)
    LIME Machine learning interpretability Mli
    +9
    這是使用LIME計算說明的示例。 選擇了XGBoost模型，但是可以使用任何模型及其Learner和Predictor節點集。 -閱讀有關葡萄酒的數據集 -在訓練和測試中對數據進行分區 -選擇一些測試集實例行進行解釋 -在輸入表中為每個實例創建本地樣本（LI…
    jamestsai > Public > 01_Compute_LIMEs
    0
    jamestsai
  19. Workflow
    Explaining the Credit Scoring Model with Model Interpretability Components
    AutoML Integrated deployment XAI
    +4
    This workflow demonstrates the usage of the verified components developed to interpret machine learning models. In the example, t…
    lada > Public > XAI > 02_XAI_Credit_Scoring_Example
    0
    lada
  20. Workflow
    Explaining the Credit Scoring Model with the XAI View
    AutoML Integrated deployment XAI
    +11
    In the example, the Credit Scoring data set is partitioned to training and test samples. Then, the black box model (Neural Networ…
    lada > Public > XAI > 05_XAI_Credit_Scoring_Example_XAI_View
    0
    lada