Hub

27 results

Filter
Fraud detection
Fraud Banking Credit card Anomaly detection Deployment
+4
  1. Workflow
    Outlier Detection in Medical Claims
    Fraud detection Outlier detection
    This workflow identifies outliers in medical claim data such as claims with an unusual high cost for a certain disease. Firstly, …
    knime > Examples > 50_Applications > 14_Medical_Claims > 01_Interactive_Outlier_Detection
    2
  2. Workflow
    Keras Autoencoder for Fraud Detection - Training
    Autoencoder Keras Neural network
    +12
    This workflow trains an autoendcoder model to detect fraudulent transactions.
    kathrin > Codeless Deep Learning with KNIME > Chapter 5 > 01_Autoencoder_for_Fraud_Detection_Training
    1
  3. Workflow
    Keras Autoencoder for Fraud Detection Training
    Autoencoder Keras Neural network
    +16
    Partition numeric input data into a training, test, and validation set. Normalize the data into range [0,1]. Build a Keras autoen…
    knime > Examples > 50_Applications > 39_Fraud_Detection > 03_Keras_Autoencoder_for_Fraud_Detection_Training
    1
  4. Workflow
    Autoencoder MNIST MidPoint Focus
    Autoencoder Keras Neural network
    +8
    Exploring the latent space of an autoencoder for dimensional reduction
    iceman > Public > Autoencoder MNIST MidPoint Focus
    1
  5. Workflow
    Outlier Dection / Fraud Detection in Contracts
    Fraud detection Anomaly detection Text processing
    +4
    Discover anomalies / irregularities / Frauds(?) in contracts payment amounts via: - data visualization - basic stats - clustering…
    rs1 > Public > Contracts_Fraud_Detection_Usecase_example
    1
  6. Workflow
    Keras Autoencoder for Fraud Detection - Deployment
    Autoencoder Keras Neural network
    +15
    This workflow applies a trained autoencoder model to detect fraudulent transactions.
    kathrin > Codeless Deep Learning with KNIME > Chapter 5 > 02_Autoencoder_for_Fraud_Detection_Deployment
    1
  7. Workflow
    Keras Autoencoder for Fraud Detection Deployment
    Autoencoder Keras Neural network
    +16
    Read Keras model. Read deployment data, which are normalized into range [0,1]. Apply the Keras model to the deployment data, calc…
    knime > Examples > 50_Applications > 39_Fraud_Detection > 04_Keras_Autoencoder_for_Fraud_Detection_Deployment
    1
  8. Workflow
    Different options to train an autoencoder using TensorFlow 2
    Autoencoder Keras Neural network
    +5
    This workflow shows the different options of training and executing a network using TF2 on the example of an autoencoder: Option …
    knime > Examples > 04_Analytics > 14_Deep_Learning > 04_TensorFlow2 > 02_Tensorflow2_Autoencoder_for_Fraud_Detection_Training
    1
  9. Workflow
    Fraud Detection: Model Deployment
    Fraud Fraud detection Random forest
    +5
    This workflow, the deployment workflow, reads the trained model, as well as the new transaction and applies the model to classify…
    knime > Examples > 50_Applications > 39_Fraud_Detection > 02_Fraud_Detection_Deployment
    1
  10. Workflow
    Keras Autoencoder for Fraud Detection - Integrated Deployment Call
    Autoencoder Keras Neural network
    +16
    This workflow executes the model generated by the Integrated deployment to get a prediction of fraudolent transaction.
    knime > Education > Courses > L4-DL Introduction to Deep Learning > Supplementary workflows > Autoencoder > 02_Fraud_Detection_Call
    0
  11. 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
  12. Workflow
    Fraud Detection by Unsupervised Learning
    Fraud Fraud detection Banking
    +8
    This workflow reads in the creditcard.csv file and trains and evaluates an Isolation Forest model that detects fraudulent transac…
    knime > Education > Learnathons > Fraud_Detection_Tutorial > Exercises > 02_Fraud_Detection_by_Unsupervised_Learning
    0
  13. Workflow
    Fraud Detection: Model Training
    Fraud Fraud detection Random forest
    +5
    This workflow reads in the creditcard.csv file and trains and evaluates a Random Forest model to classify transactions as either …
    knime > Examples > 50_Applications > 39_Fraud_Detection > 01_Fraud_Detection_Model_Training
    0
  14. Workflow
    Keras Autoencoder for Fraud Detection - Deployment
    Autoencoder Keras Neural network
    +16
    Exercise of the L4-DL Introduction to Deep Learning Course. The goal of this exercise is to apply a trained autoencoder to new tr…
    knime > Education > Courses > L4-DL Introduction to Deep Learning > Session2 > Exercises > 02_Fraud_Detection_Deployment
    0
  15. Workflow
    Fraud Detection: Table Input
    Fraud Fraud detection Random forest
    +6
    This workflow showcases how the Container Input (Table) and Container Output (Table) nodes can be used to create a REST API for a…
    jtyler > KNIME-Edge-Server-Workflows > Example_Use_Cases > General > Fraud Detection > 02_Fraud_Detection_Table_Input
    0
  16. Workflow
    Fraud Detection: Row Input
    Fraud Fraud detection Random forest
    +6
    This workflow showcases how the Container Input (Row) and Container Output (Row) nodes can be used to create a REST API for a wor…
    jtyler > KNIME-Edge-Server-Workflows > Example_Use_Cases > General > Fraud Detection > 01_Fraud_Detection_Row_Input
    0
  17. Workflow
    Fraud Detection: JSON Input
    Fraud Fraud detection Random forest
    +6
    This workflow showcases how the Container Input (JSON) and Container Output (JSON) nodes can be used to create a REST API for a w…
    jtyler > KNIME-Edge-Server-Workflows > Example_Use_Cases > General > Fraud Detection > 04_Fraud_Detection_JSON_Input
    0
  18. Workflow
    Fraud Detection: Model Deployment
    Fraud Fraud detection Random forest
    +1
    This workflow, the deployment workflow, reads the trained model, as well as the new transaction and applies the model to classify…
    kathrin > Public > Faud_Detection_Autoencoder > Isolation_Forest_for_Fraud_Detection_Deployment
    0
  19. Workflow
    Fraud Detection by Unsupervised Learning
    Fraud Fraud detection Banking
    +8
    This workflow reads in the creditcard.csv file and trains and evaluates an Isolation Forest model that detects fraudulent transac…
    knime > Education > Learnathons > Fraud_Detection_Tutorial > Solutions > 02_Fraud_Detection_by_Unsupervised_Learning
    0
  20. Workflow
    Fraud Detection: Row and Variable Input
    Fraud Fraud detection Random forest
    +6
    This workflow showcases how the Container Input (Row), Container Input (Variable) and Container Output (JSON) nodes can be used t…
    jtyler > KNIME-Edge-Server-Workflows > Example_Use_Cases > General > Fraud Detection > 03_Fraud_Detection_Row_And_Variable_Input
    0