Hub
  • Software
  • Blog
  • Forum
  • Events
  • Documentation
  • About KNIME
  • KNIME Hub
  • Search

48 results

Filter
Logistic regression
Classification Education Machine Learning Parameter optimization Random Forest
+3
  1. Go to item
    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
  2. Go to item
    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. Go to item
    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
  4. Go to item
    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
  5. Go to item
    Workflow
    Training a Churn Predictor - Logistic Regression
    Classification Logistic regression
    This workflow is an example of how to build a basic classification model for a churn prediction using a logistic regression algor…
    alinebessa > Courses and Workshops > Norbert and Michael - Workshop > ChurnPrediction > Logistic Regression Model
    0
  6. Go to item
    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. Go to item
    Workflow
    Logistic Regression
    Logistic regression Classification Education
    +4
    Logistic Regression: predict wine color. - Normalize numerical columns - Partition the dataset into train and test set - Train a …
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter8_Regression > Logistic_Regression_Solution
    0
  8. Go to item
    Workflow
    Logistic Regression on wine dataset
    Logistic regression Classification Training
    This workflow preprocesses data and trains a logistic regression to predict wine color. Performance is assessed with a Scorer nod…
    emilio_s > Simple Examples > 2. Logistic Regression on wine dataset
    0
  9. Go to item
    Workflow
    17_Logistic_Regression - Solution
    E-learning Logistic regression Classification
    +1
    Solution to an e-learning course exercise. Train a logistic regression model.
    stervis > Public > E-Learning > L1-DS KNIME Analytics Platform for Data Scientists - Basics > Solutions > 17_Logistic_Regression - Solution
    0
  10. Go to item
    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 > Solutions > 01_Fraud_Detection_by_Supervised_Learning
    0
  11. Go to item
    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
  12. Go to item
    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
  13. Go to item
    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
  14. Go to item
    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
  15. Go to item
    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
  16. Go to item
    Workflow
    Logistic Regression
    Logistic regression Classification Education
    +4
    Logistic Regression: predict wine color. - Normalize numerical columns - Partition the dataset into train and test set - Train a …
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter8_Regression > Logistic_Regression_Exercise
    0
  17. Go to item
    Workflow
    Feature Selection
    Forward feature selection Classification Logistic regression
    +1
    Introduction to Machine Learning Algorithms course - Session 4 Exercise 5 - Combine previously splitted train and test set - Sear…
    knime > Education > Courses > L4-ML Introduction to Machine Learning Algorithms > Session_4 > 01_Exercises > 05_Feature_Selection
    0
  18. Go to item
    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
  19. Go to item
    Workflow
    Logistic Regression
    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
  20. Go to item
    Workflow
    Logistic Regression - Solution
    Classification Logistic regression Education
    Introduction to Machine Learning Algorithms course - Session 2 Solution to exercise 4 - Train a logistic regression model - Apply…
    knime > Education > Courses > L4-ML Introduction to Machine Learning Algorithms > Session_2 > 02_Solutions > 04_Logistic_Regression_solution
    0

KNIME
Open for Innovation

KNIME AG
Hardturmstrasse 66
8005 Zurich, Switzerland
  • Software
  • Getting started
  • Documentation
  • E-Learning course
  • Solutions
  • KNIME Hub
  • KNIME Forum
  • Blog
  • Events
  • Partner
  • Developers
  • KNIME Home
  • KNIME Open Source Story
  • Careers
  • Contact us
Download KNIME Analytics Platform Read more on KNIME Server
© 2022 KNIME AG. All rights reserved.
  • Trademarks
  • Imprint
  • Privacy
  • Terms & Conditions
  • Credits