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Cross-validation
ROC Bayesian optimization CI Cohen's Kappa Customer Intelligence Feature Engineering GIDS H2O
  1. Workflow
    H2O Cross-Validation
    H2O Machine learning Cross-validation
    This workflow shows how to use cross-validation in H2O using the KNIME H2O Nodes. In the example we use the H2O Random Forest to …
    knime > Examples > 04_Analytics > 15_H2O_Machine_Learning > 04_H2O_Crossvalidation
    1
    knime
  2. Workflow
    Training and Testing a Model (decision tree)
    TheGuideBook Decision tree Testing
    +11
    This workflow shows how to train and test a basic classification model. Using the adult dataset, a decision tree is trained and t…
    knime > Academic Alliance > Guide to Intelligent Data Science > Example Workflows > Chapter5 > 01_CrossValidation_Scorer_ROC
    0
    knime
  3. Workflow
    Training a Churn Predictor
    Customer Intelligence CI Churn
    +5
    This workflow is an example of how to train a basic machine learning model for a churn prediction task. In this case we train a r…
    knime > Machine Learning and Marketing > Consumer Behavior > Churn Prediction > 01_Creating_a_Churn_Predictor
    0
    knime
  4. 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
    ashokharnal