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XGBoost
Knime Automl H2o H2o.ai Learning
+3
  1. Go to item
    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
  2. Go to item
    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
  3. Go to item
    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
  4. Go to item
    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
  5. Go to item
    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
  6. Go to item
    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
  7. Go to item
    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
  8. Go to item
    Workflow
    H2O.ai AutoML (generic KNIME nodes) in KNIME for regression problems - a powerful auto-machine-learning framework
    H2o Automl Knime
    +9
    H2O.ai AutoML (generic KNIME nodes) in KNIME for regression problems - a powerful auto-machine-learning framework (https://hub.kn…
    mlauber71 > Public > automl > kn_automl_h2o_regression
    0
  9. Go to item
    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
  10. Go to item
    Workflow
    (forum example) H2O.ai AutoML (wrapped with R) with vtreat data preparation in KNIME for classification problems (with R vtreat)
    H2o Automl Knime
    +10
    H2O.ai AutoML (wrapped with R) with vtreat data preparation in KNIME for classification problems (with R vtreat) - a powerful aut…
    mlauber71 > Public > forum > kn_forum_automl_h2o_classification_r_vtreat_svm
    0
  11. Go to item
    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
  12. Go to item
    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
  13. Go to item
    Workflow
    H2O.ai AutoML (wrapped with R) with vtreat data preparation in KNIME for regression problems
    H2o Automl Knime
    +11
    H2O.ai AutoML (wrapped with R) with vtreat data preparation in KNIME for regression problems (with R vtreat) - a powerful auto-ma…
    mlauber71 > Forum > 2022 > kn_forum_39929_video_h2o_regression_r_vtreat
    0
  14. Go to item
    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 > Exercises > 02_Hyperparameter Optimization
    0
  15. Go to item
    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_Bonus
    0
  16. Go to item
    Workflow
    H2O.ai AutoML (wrapped with R community nodes) in KNIME for classification problems (with R vtreat)
    H2o Automl Knime
    +12
    H2O.ai AutoML (wrapped with R community nodes) in KNIME for classification problems (with R vtreat) - a powerful auto-machine-lea…
    mlauber71 > Forum > 2022 > kn_forum_38612_h2o_ecg_classification_r_vtreat
    0
  17. Go to item
    Workflow
    xgboost parameter tuning and handling large datasets
    Xgboost Handling large datasets ROC
    +5
    This example demonstrates following: 1. Handling Large datasets in KNIME--Setting Memory Policy 2. Feature Engineering 3. ROC cur…
    ashokharnal > Collection of Components and Workflows > xgboost parameter tuning using Bayes Optimization > xgboost parameter tuning (maximise ROC) using Bayes Optimization
    0
  18. Go to item
    Workflow
    H2O.ai AutoML (wrapped with R) with vtreat data preparation in KNIME for regression problems
    H2o Automl Knime
    +11
    H2O.ai AutoML (wrapped with R) with vtreat data preparation in KNIME for regression problems (with R vtreat) - a powerful auto-ma…
    mlauber71 > Public > automl > kn_automl_h2o_regression_r_vtreat
    0
  19. Go to item
    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
  20. Go to item
    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…
    lyudmila > Public > Mixing_DL_with_XGBoost
    0

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