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Knime Automl H2o H2o.ai Learning Machine Auto Machine learning Analytics Integrations
  1. Workflow
    Validating KNIME Workflows
    Reproducibility Validation Testing
    +3
    This workflow demonstrates a technique to deploy a model prediction workflow as a web service and to validate that it is doing wh…
    knime > Examples > 50_Applications > 51_Model_Deployment_and_Validation > 01_Deploying_and_Validating_models_as_WebServices
    3
    greglandrum
  2. Workflow
    Mixing Deep Learning with XGBoost
    Deep Learning Machine Learning XGBoost
    +11
    This workflow shows how to train an XGBoost based image classifier that uses a pretrained convolutional neural network to extract…
    christian.birkhold > My Sandbox > Mixing_DL_with_XGBoost
    1
    christian.birkhold
  3. Workflow
    H2O.ai AutoML (wrapped with Python) in KNIME for regression problems
    H2o Automl Knime
    +8
    H2O.ai AutoML (wrapped with Python) in KNIME for regression problems - a powerful auto-machine-learning framework (https://hub.kn…
    mlauber71 > Public > automl > kn_automl_h2o_regression_python
    1
    mlauber71
  4. Workflow
    H2O.ai AutoML (wrapped with R) in KNIME for regression problems
    H2o Automl Knime
    +8
    H2O.ai AutoML (wrapped with R) in KNIME for regression problems - a powerful auto-machine-learning framework (https://hub.knime.c…
    mlauber71 > Public > automl > kn_automl_h2o_regression_r
    1
    mlauber71
  5. Workflow
    Housing Value Prediction using XGBoost for Regression
    XGBoost Regression Gradient boosting
    +5
    This workflow shows how the XGBoost nodes can be used for regression tasks. It also demonstrates a combination of parameter optim…
    knime > Examples > 04_Analytics > 16_XGBoost > 02_Housing_Value_Regression_with_XGBoost
    1
    nemad
  6. 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
  7. Workflow
    use Python XGBoost package to build model and deploy that thru KNIME Python nodes
    Xgboost Python Model
    +2
    use Python XGBoost package to build model and deploy that thru KNIME Python nodes in the subfolder /data/ there is a Jupyter note…
    mlauber71 > Public > kn_example_python_xgboost
    1
    mlauber71
  8. Node / Predictor
    XGBoost Predictor
    Analytics Integrations XGBoost
    +1
    Applies a classification XGBoost model to predict data.
    1
    knime
  9. Node / Predictor
    XGBoost Predictor (Regression)
    Analytics Integrations XGBoost
    +1
    Applies a regression XGBoost model to predict data.
    1
    knime
  10. 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
  11. Workflow
    H2O.ai AutoML (wrapped with Python) in KNIME for regression problems
    H2o Automl Knime
    +8
    H2O.ai AutoML (wrapped with Python) in KNIME for regression problems - a powerful auto-machine-learning framework (https://hub.kn…
    anna_k > Public > kn_automl_h2o_regression_python
    0
    anna_k
  12. Workflow
    XAI View Component with a Custom Model
    Guided analytics Integrated deployment XAI
    +7
    This application is a simple example of Xgboost model with KNIME Software for binary and multiclass classification. The model out…
    k10shetty1 > XAI Space > Classification > Custom Models > 02_Explainable_Artificial_Intelligence_(XAI)
    0
    k10shetty1
  13. Workflow
    Model Selection with Integrated Deployment
    Chemistry Naive bayes Random forest
    +11
    This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementation the c…
    knime > Education > Courses > L4-CA Machine Learning for Chemical Applications > Solutions > 02_Hyperparameter Optimization
    0
    alice_krebs
  14. Workflow
    H2O.ai AutoML (wrapped with R) in KNIME for regression problems
    H2o Automl Knime
    +8
    H2O.ai AutoML (wrapped with R) in KNIME for regression problems - a powerful auto-machine-learning framework (https://hub.knime.c…
    l20121 > Public > kn_automl_h2o_regression_r
    0
    l20121
  15. Workflow
    Mixing Deep Learning with XGBoost
    Deep Learning Machine Learning XGBoost
    +11
    This workflow shows how to train an XGBoost based image classifier that uses a pretrained convolutional neural network to extract…
    yusupov > Public > Mixing_DL_with_XGBoost
    0
    yusupov
  16. Workflow
    Model Selection with Integrated Deployment
    Chemistry Naive bayes Random forest
    +11
    This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementation the c…
    janina > Public > 2022_01_KNIME_User_Day > Model Selection with Integrated Deployment
    0
    janina
  17. Workflow
    Model Selection with Integrated Deployment
    Chemistry Naive bayes Random forest
    +11
    This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementation the c…
    knime > Life Sciences > Events > 2020_10_Integrated_Deployment_In_Action_Webinar > Model Selection with Integrated Deployment
    0
    knime
  18. Workflow
    s_618 - H2O.ai AutoML (generic KNIME nodes) in KNIME for classification problems - a powerful auto-machine-learning framework applied via Sparkling Water on a Big Data system
    H2o Automl Knime
    +10
    s_618 - H2O.ai AutoML (generic KNIME nodes) in KNIME for classification problems - a powerful auto-machine-learning framework app…
    mlauber71 > Public > kn_example_bigdata_h2o_automl_spark_46 > s_618_h2o_automl_spark
    0
    mlauber71
  19. 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
  20. Workflow
    H2O.ai AutoML (wrapped with R) in KNIME for classification problems
    H2o Automl Knime
    +3
    H2O.ai AutoML (wrapped with R) in KNIME for classification problems - a powerful auto-machine-learning framework https://hub.knim…
    mlauber71 > Public > kn_example_bigdata_h2o_automl_spark > s_415_h2o_automl_classification_r
    0
    mlauber71