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Random forest
Ensemble model Machine learning Classification Banking Parameter optimization
+10
  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
  2. Workflow
    Taxi demand prediction training workflow
    Demand prediction Random forest Time series prediction
    +5
    In this use case, we will use the NYC taxi dataset and a Random Forest to train a simple time series prediction model to predict …
    knime > Examples > 10_Big_Data > 02_Spark_Executor > 11_Taxi_Demand_Prediction > Training_workflow
    3
  3. Workflow
    Taxi demand prediction deployment
    Demand prediction Random forest Time series prediction
    +5
    In this use case, we will use the NYC taxi dataset and a Random Forest to train a simple time series prediction model to predict …
    knime > Examples > 10_Big_Data > 02_Spark_Executor > 11_Taxi_Demand_Prediction > Deployment_workflow
    2
  4. Workflow
    Overview of Credit Card Fraud Detection Techniques
    Credit card Fraud DBSCAN
    +8
    This workflow shows an overview of credit card fraud detection techniques. The performances of the techniques are evaluated on th…
    knime > Finance, Accounting, and Audit > Overview of Credit Card Fraud Detection Techniques
    1
  5. Workflow
    Risk Scoring: Estimation of Probability of Default
    Risk Scoring Risk assessment
    +5
    The probability of default is a metric that lenders use to assess risk on customers, group them into similar risk bands, and dete…
    knime > Examples > 50_Applications > 38_Credit_Risk_Assessment > Credit_Scoring_Training
    1
  6. Workflow
    Fraud Detection: Model Deployment
    Fraud Fraud detection Random forest
    +5
    This workflow, the deployment workflow, reads the trained model, as well as the new transaction and applies the model to classify…
    knime > Examples > 50_Applications > 39_Fraud_Detection > 02_Fraud_Detection_Deployment
    1
  7. Workflow
    Training a Decision Tree
    Classification Machine learning Prediction
    +9
    Training a decision tree and training a random forest of decision trees. Adult.csv dataset describes US census information. Outpu…
    rs1 > Public > 09_Random_Forest
    1
  8. Workflow
    Applying Optimized Threshold from Binary Calssification Inspector
    Machine Learning Classification Data Mining
    +7
    This workflow is made to show how to apply the threshold computed by the Binary Classification Inspector for new data. the thresh…
    paolotamag > Public > Applying_Optimized_Threshold_from_Binary_Calssification_Inspector
    1
  9. Workflow
    Training a Random Forest
    Classification Machine learning Prediction
    +11
    Training a decision tree and training a random forest of decision trees.
    knime > Examples > 04_Analytics > 04_Classification_and_Predictive_Modelling > 09_Random_Forest
    1
  10. Workflow
    Lean Restocking Alert Signal: Training
    Backward feature elimination Random forest Decision tree
    +7
    This workflow implements an alarm system for bycicle restocking at Washington bike stations. The dataset is the bike dataset. Pro…
    knime > Examples > 50_Applications > 55_Bike_Restocking_Alert > 01_Bike_Restocking_Alert_Training_w_Feature_Selection
    1
  11. Workflow
    Random Forest, Gradient Boosted Trees, and TreeEnsemble
    Classification Machine learning Prediction
    +9
    This workflow solves a binary classification problem on the adult dataset using more advanced algorithms: - Random Forest - Gradi…
    rs1 > Public > Tree_Ensembles
    1
  12. Workflow
    07 Random Forest
    Ensemble model Random Forest
    Exercise for training a Random Forest model. Build a Random Forest (Regression) model on a training set. Apply it to a test set, …
    galaxius237 > hannigtp_IT4015C > Lab-4-Full > L2-DS Exercises > 07 Random Forest
    0
  13. Workflow
    07 Random Forest
    Ensemble model Random Forest
    Exercise for training a Random Forest model. Build a Random Forest (Regression) model on a training set. Apply it to a test set, …
    kellej6 > IT4015 Applied Business Intelligence > Lab 4 > L4-WA_Fn-UseC_-IT-Help-Desk > Exercises > 07 Random Forest
    0
  14. Workflow
    07 Random Forest
    Ensemble model Random Forest
    Exercise for training a Random Forest model. Build a Random Forest (Regression) model on a training set. Apply it to a test set, …
    natand51 > Public > Lab4-NathanAnderson > Tutorial Data > Exercises > 07 Random Forest
    0
  15. Workflow
    07 Random Forest
    Ensemble model Random Forest
    Exercise for training a Random Forest model. Build a Random Forest (Regression) model on a training set. Apply it to a test set, …
    zangyun_928 > Public > L2-DS KNIME Analytics Platform for Data Scientists - Advanced > Exercises > 07 Random Forest
    0
  16. Workflow
    07 Random Forest - Solution
    Ensemble model Random Forest
    Solution to an exercise for training a Random Forest model. Build a Random Forest (Regression) model on a training set. Apply it …
    baileke > IT 4015 Baileke Projects > L2-DS KNIME Analytics Platform for Data Scientists - Advanced > Solutions > 07 Random Forest - Solution
    0
  17. Workflow
    07 Random Forest - Solution
    Ensemble model Random Forest
    Solution to an exercise for training a Random Forest model. Build a Random Forest (Regression) model on a training set. Apply it …
    fuschiefox > IT 4015 snavelmy Projects > IT 4015 Project 4 > extra_data > extra 07 Random Forest
    0
  18. Workflow
    2018-2020_Bike_Restocking_c8y_v4.1
    Random forest Decision tree Linear correlation
    +6
    Lean Restocking Alert System: Combining Cumulocity (to manage IoT Devices, in this case bicycles) with KNIME (to visualize and an…
    dietrich_wettschereck > Public > 2018-2020_Bike_Restocking_c8y_v4.1
    0
  19. Workflow
    Advanced Machine Learning - Chemistry
    Machine learning Data mining Classification
    +11
    "Advanced Machine Learning Chemistry" exercise for the advanced Life Science User Training - Training a Random Forest model to pr…
    catherineoleary > Public > L2-LS KNIME Analytics Platform for Data Scientists - Life Sciences - Advanced > Exercises > 03. Advanced Machine Learning Chemistry
    0
  20. Workflow
    Fraud Detection: Row Input
    Fraud Fraud detection Random forest
    +6
    This workflow showcases how the Container Input (Row) and Container Output (Row) nodes can be used to create a REST API for a wor…
    jtyler > KNIME-Edge-Server-Workflows > Example_Use_Cases > General > Fraud Detection > 01_Fraud_Detection_Row_Input
    0