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Logistic regression
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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
    knime
  2. 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
    knime
  3. Workflow
    Assessing Effects of Single Predictors with Delta-p
    Logistic regression Post estimation Delta-p
    +1
    This workflow calculates the Delta-p statistics based on the coefficient statistics of a logistic regression model. The Delta-p s…
    knime > Examples > 04_Analytics > 10_Scoring > 06_Assessing_Effects_of_Single_Predictors_with_Delta-p
    1
    knime
  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
    paolotamag
  5. Workflow
    Attribution Models: Touch-based, Correlation and Regression, Shapley-based, and Randomized field experiments
    Marketing Analytics Attribution Models Logistic Regression
    +3
    This workflow is based on the book chapter "Attribution Modelling" by de Haan (2022). It replicates the analysis of the book chap…
    knime > Machine Learning and Marketing > Attribution Models > Attribution Models - Touch-based, Correlation and Regression, Shapley-based, and Randomized field experiments
    1
    knime
  6. Workflow
    17_Logistic_Regression
    E-learning Logistic regression Classification
    +1
    E-learning course exercise. Train a logistic regression model.
    stervis > Public > E-Learning > L1-DS KNIME Analytics Platform for Data Scientists - Basics > Exercises > 17_Logistic_Regression
    0
    stervis
  7. Workflow
    17_Logistic_Regression
    E-learning Logistic regression Classification
    +1
    E-learning course exercise. Train a logistic regression model.
    mavalenciaor > Public > L1-DS KNIME Analytics Platform for Data Scientists - Basics > Exercises > 17_Logistic_Regression
    0
    mavalenciaor
  8. 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
    hayasaka
  9. 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
    svbaranov
  10. Workflow
    Logistic Regression - exercise
    Classification Logistic regression Education
    Introduction to Machine Learning Algorithms course - Session 2 Exercise 4 - Train a logistic regression model - Apply the model t…
    knime > Education > Courses > L4-ML Introduction to Machine Learning Algorithms > Session_2 > 01_Exercises > 04_Logistic_Regression
    0
    hayasaka
  11. Workflow
    17_Logistic_Regression
    E-learning Logistic regression Classification
    +1
    E-learning course exercise. Train a logistic regression model.
    a2620 > Public > L1-DS KNIME Analytics Platform for Data Scientists - Basics > Exercises > 17_Logistic_Regression
    0
    a2620
  12. 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
    maarit
  13. 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
    knime
  14. Workflow
    17_Logistic_Regression - Solution
    E-learning Logistic regression Classification
    +1
    Solution to an e-learning course exercise. Train a logistic regression model.
    a2620 > Public > L1-DS KNIME Analytics Platform for Data Scientists - Basics > Solutions > 17_Logistic_Regression - Solution
    0
    a2620
  15. 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
    atomnous
  16. 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
    janina
  17. Workflow
    Feature Selection - Solution
    Forward feature selection Classification Logistic regression
    +1
    Introduction to Machine Learning Algorithms course - Session 4 Solution to exercise 5 - Combine previously splitted training and …
    hayasaka > L4-ML-2Hrs-2021-07 > Solutions > 08_Feature_Selection_solution
    0
    hayasaka
  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…
    kathrin > Public > Regularized_Logistic_Regression > 08_Regularized_Logistic_Regression
    0
    kathrin
  19. 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
    knime
  20. Workflow
    Logistic Regression (verificare se si è in overfitting)
    Classification Machine learning Prediction
    +6
    Per verificare se i valori elevati di accuratezza dell'algoritmo Logistic regression non siano dovuti ad overfitting, in questa v…
    falaimo > Public > KNIME Analytics Platform per Data Scientists, corso base > 06_Logistic_Regression (check overfitting)
    0
    falaimo