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Random Forest
Machine learning
Classification Parameter optimization Data science KNIME Prediction
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  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
    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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. Workflow
    Classification of written letters with a Random Forest
    Classification Machine learning Prediction
    +7
    Training a random forest to classify written letters. This is the solution to the exercise in the KNIME e-learning course under h…
    rs1 > Public > Clax_Written_Letters_Random_Forest
    0
  9. 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
  10. Workflow
    Group 2 Training, Evaluation and Optimization
    Predictive Analytics Machine Learning Parameter Optimization
    +6
    Solution to the tasks for Group 2 in KNIME Data Science Learnathon - Train a Decision Tree on the training set, and apply the mod…
    knime > Education > Learnathons > From_Raw_Data_To_Deployment > Learnathon > Challenges > Group2_Training_Evaluation_and_Optimization > Group2_1_Training_Evaluation_and_Optimization
    0
  11. Workflow
    Parameter Optimization Component Hardcoded on Random Forest (Legacy)
    Machine learning Data science Random forest
    +2
    This workflow shows how to use the legacy version of the parameter optimization component. This component only works out of the b…
    k10shetty1 > Parameter Optimization for Classification > 02_Parameter_Optimization_with_Components > 00_Parameter_Optimization_Component_Hardcoded_on_Random_Forest_(Legacy)
    0
  12. Workflow
    W7_Machine_learning
    Ligand-based screening Machine learning Random forest
    +2
    With the continuously increasing amount of available compound, bioactivity and structural data, machine learning (ML) gained mome…
    tymsk3891 > Public > TeachOpenCADD_reconfigured_with_KNIME_4.5 > Workflow > W7_Machine_learning
    0
  13. Workflow
    Parameter Optimization (Table) Component on Random Forest
    Parameter optimization Machine learning Random forest
    +4
    This workflow shows an example for the "Parameter Optimization (Table)" component (kni.me/c/dIpKMJbiO-3019eb). The model used for…
    k10shetty1 > Parameter Optimization for Classification > 02_Parameter_Optimization_with_Components > 01_Parameter_Optimization_(Table)_Component_on_Random_Forest
    0
  14. Workflow
    Analyzing Churn Models with the Binary Classification Inspector
    Machine Learning Classification Data Mining
    +7
    This workflow demonstrates the functionality of the Binary Classification Inspector node. It produces a complex view made of four…
    atomnous > Public > 04_Classification_and_Predictive_Modelling > 10_Analyzing_Churn_Models_with_the_Binary_Classification_Inspector
    0
  15. Workflow
    Training a Random Forest
    Classification Machine learning Prediction
    +9
    Training a decision tree and training a random forest of decision trees.
    sebastian_sauer > Public > titanic-rf1
    0
  16. 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…
    svbaranov > Public > Applying_Optimized_Threshold_from_Binary_Calssification_Inspector
    0
  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 > Education > Courses > L4-CA Machine Learning for Chemical Applications > Exercises > 02_Hyperparameter Optimization
    0
  18. Workflow
    Random Forest, Gradient Boosted Trees, and TreeEnsemble
    Classification Machine learning Prediction
    +11
    This workflow solves a binary classification problem on the adult dataset using more advanced algorithms: - Random Forest - Gradi…
    knime > Academic Alliance > Guide to Intelligent Data Science > Example Workflows > Chapter9 > 04_TreeEnsemble
    0
  19. 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
  20. 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…
    knime > Education > Courses > L2-LS KNIME Analytics Platform for Data Scientists - Life Sciences - Advanced > Exercises > 03. Advanced Machine Learning Chemistry
    0