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Logistic regression
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Decision Tree Random Forest Scoring Data science Parameter optimization
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  1. Workflow
    Logistic Regression
    Classification Machine learning Prediction
    +5
    This workflow is an example of how to build a basic prediction / classification model using logistic regression.
    knime > Examples > 04_Analytics > 04_Classification_and_Predictive_Modelling > 06_Logistic_Regression
    2
  2. 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
  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…
    svbaranov > Public > Applying_Optimized_Threshold_from_Binary_Calssification_Inspector
    0
  4. 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-Solutions > Group2_Training_Evaluation_and_Optimization > Group2_1_Training_Evaluation_and_Optimization
    0
  5. Workflow
    Impact of Regularization in case of Logistic Regression
    Regularization Gauss Laplace
    +5
    The goal of this workflow is to analyze the impact of different priors in case of the logistic regression. The workflow therefore…
    atomnous > Public > 04_Classification_and_Predictive_Modelling > 08_Regularized_Logistic_Regression
    0
  6. Workflow
    Logistic Regression
    Classification Machine learning Prediction
    +5
    This workflow is an example of how to build a basic prediction / classification model using logistic regression.
    atomnous > Public > 04_Classification_and_Predictive_Modelling > 06_Logistic_Regression
    0
  7. Workflow
    Logistic Regression with Spark
    Classification Machine learning Prediction
    +5
    This workflow is builds a classification model using logistic regression in SPARK.
    knime > Examples > 10_Big_Data > 02_Spark_Executor > 15_Logistic_Regression_with_Spark
    0
  8. Workflow
    Parameter Optimization Loop with Cross Validation
    Parameter optimization Optimization Machine learning
    +5
    This workflow shows an example of parameter optimization in a logistic regression model. In the logistic regression we optimize s…
    k10shetty1 > Parameter Optimization for Classification > 01_Parameter_Optimization_with_Nodes > 03_Parameter_Optimization_Loop_on_Logit_with_CV
    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_Bonus
    0
  10. 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
  11. 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
  12. Workflow
    Weak Supervision on the Adult dataset
    Weak Supervision Weakly Supervised Learning Machine Learning
    +4
    This workflow shows how to use the Weak Label Model Learner and Predictor nodes to aggregate sources of weak supervision such as …
    knime > Examples > 04_Analytics > 13_Meta_Learning > 05_Weak_Supervision_on_the_Adult_dataset
    0
  13. 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…
    knime > Examples > 04_Analytics > 04_Classification_and_Predictive_Modelling > 10_Analyzing_Churn_Models_with_the_Binary_Classification_Inspector
    0
  14. 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
  15. 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
  16. Workflow
    Impact of Regularization in case of Logistic Regression
    Regularization Gauss Laplace
    +5
    The goal of this workflow is to analyze the impact of different priors in case of the logistic regression. The workflow therefore…
    kathrin > Public > Regularized_Logistic_Regression > 08_Regularized_Logistic_Regression
    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 > Life Sciences > Events > 2020_10_Integrated_Deployment_In_Action_Webinar > Model Selection with Integrated Deployment
    0
  18. Workflow
    Impact of Regularization in case of Logistic Regression
    Regularization Gauss Laplace
    +5
    The goal of this workflow is to analyze the impact of different priors in case of the logistic regression. The workflow therefore…
    knime > Examples > 04_Analytics > 04_Classification_and_Predictive_Modelling > 08_Regularized_Logistic_Regression
    0
  19. Workflow
    Group 2 Training, Evaluation and Optimization
    Predictive Analytics Machine Learning Parameter Optimization
    +6
    Tasks for Group 2 in KNIME Data Science Learnathon - Train a Decision Tree on the training set, and apply the model to the test s…
    maarit > University Course > Learnathon UM April 21 > Challenges > Group2_Training_Evaluation_and_Optimization > Group2_1_Training_Evaluation_and_Optimization
    0
  20. 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