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Random forest
Classification
Machine learning Bagging Prediction KNIME Analytics
+4
  1. 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
  2. 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
  3. 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
  4. 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
  5. Workflow
    06_Random_Forest
    E-learning Classification Tree ensemble
    +2
    E-learning course exercise. Train a Random Forest model to predict letters based on their image characteristics.
    burdhasp > Public > Exercises - L2-DS KNIME Analytics Platform for Data Scientists - Advanced > Exercises > 06_Random_Forest
    0
  6. Workflow
    06_Random_Forest - Solution
    E-learning Classification Tree ensemble
    +2
    Solution to an e-learning course exercise. Train a Random Forest model to predict letters based on their image characteristics.
    stervis > Public > E-Learning > L2-DS KNIME Analytics Platform for Data Scientists - Advanced > Solutions > 06_Random_Forest - Solution
    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
    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
  10. 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
  11. 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
  12. Workflow
    06_Random_Forest - Solution
    E-learning Classification Tree ensemble
    +2
    Solution to an e-learning course exercise. Train a Random Forest model to predict letters based on their image characteristics.
    burdhasp > Public > Exercises - L2-DS KNIME Analytics Platform for Data Scientists - Advanced > Solutions > 06_Random_Forest - Solution
    0
  13. 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
  14. Workflow
    Ensemble methods
    Classification Random forest Gradient boosted trees
    +7
    Ensembles: binary classification of house ranking (high/low rank). - Random forest - Gradient Boosted Trees - Training - Evaluati…
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter9_Ensemble_Methods > Ensemble_Solution
    0
  15. 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
  16. Workflow
    Fraud Detection by Supervised Learning
    Fraud Fraud detection Random forest
    +9
    This workflow reads in the creditcard.csv file and trains and evaluates a Logistic Regression and a Random Forest model to classi…
    knime > Education > Learnathons > Fraud_Detection_Tutorial > Exercises > 01_Fraud_Detection_by_Supervised_Learning
    0
  17. 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
  18. Workflow
    Ensemble methods
    Classification Random forest Gradient boosted trees
    +7
    Ensembles: binary classification of house ranking (high/low rank). - Random forest - Gradient Boosted Trees - Training - Evaluati…
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter9_Ensemble_Methods > Ensemble_Exercise
    0
  19. Workflow
    06_Random_Forest
    E-learning Classification Tree ensemble
    +2
    E-learning course exercise. Train a Random Forest model to predict letters based on their image characteristics.
    stervis > Public > E-Learning > L2-DS KNIME Analytics Platform for Data Scientists - Advanced > Exercises > 06_Random_Forest
    0
  20. Workflow
    Random Forest on Titanic data set including tuning
    Classification Education Ensemble
    +3
    - Train a random forest model - Apply the model to the test set - Evaluate the model performance with the Scorer node - Perform P…
    sebastian_sauer > Public > titanic-rf2
    0