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Anomaly detection
IoT Internet of Things Time series analysis Predictive maintenance Sensor
+4
  1. Workflow
    Anomaly Detection. Control Chart
    Anomaly detection Time series analysis IoT
    +5
    This workflow performs anomaly detection using a control chart: - Calculate the "normal conditions" as the cumulative average +/-…
    knime > Examples > 50_Applications > 17_AnomalyDetection > 04_Creating_a_ControlChart_of_a_Time_Series
    3
  2. Workflow
    Anomaly Detection. Time Series AR Deployment
    Anomaly detection Time series analysis Auto-regressive models
    +7
    This workflow deploys a previously trained auto-regressive model for anomaly detection: - Select the date for deployment. Two mon…
    knime > Examples > 50_Applications > 40_Anomaly_Detection > 03_Time_Series_AR_Deployment
    2
  3. Workflow
    Anomaly Detection. Time Series AR Testing
    Anomaly detection Time series analysis Auto-regressive models
    +6
    This workflow tests the performance of previously trained auto-regressive models for anomaly detection: - Filter the data to the …
    knime > Examples > 50_Applications > 17_AnomalyDetection > 03b_Time_Series_AR_Testing
    2
  4. Workflow
    Fourier Transform for Anamoly Detection
    IoT Time Series FFT
    +5
    In this workflow I demonstrate how the Fourier Transform along with basic aggregations and rule settings can be used to automatic…
    corey > Public > Fourier Transform for Anamoly Detection
    1
  5. 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
  6. 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
  7. Workflow
    Time Series AR Training
    Anomaly detection Time series analysis Auto-regressive models
    +4
    This workflow trains an auto-regressive model for anomaly detection: - Filter the data to training data covering only normal func…
    knime > Codeless Time Series Analysis with KNIME > Chapter 11 > 02_Time_Series_AR_Training
    1
  8. Workflow
    Anomaly Detection. Control Chart
    Anomaly detection Time series analysis IoT
    +4
    This workflow performs anomaly detection using a control chart: - Calculate the "normal conditions" as the average +/- 12 times t…
    knime > Codeless Time Series Analysis with KNIME > Chapter 11 > 04_Creating_a_ControlChart_of_a_Time_Series
    1
  9. Workflow
    Send email to start checkup
    Anomaly detection Time series analysis IoT
    +1
    This workflow simply sends an email. It is called via a Call Workflow node from a parent workflow.
    knime > Codeless Time Series Analysis with KNIME > Chapter 11 > Send_Email_to_start_checkup
    1
  10. 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
  11. 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
  12. 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
  13. Workflow
    Anomaly Detection. Time Alignment & Visualization
    Anomaly detection Time series analysis Time alignment
    +7
    This workflow preprocesses and visualizes sensor data for anomaly detection: - Read FFT preprocessed data files with date, time, …
    knime > Examples > 50_Applications > 17_AnomalyDetection > 01_Preprocessing_Time_Alignment_and_Visualization
    1
  14. 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
  15. 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
  16. Workflow
    Anomaly Detection: Time Alignment & Visualization
    Anomaly detection Time series analysis Time alignment
    +2
    This workflow performs time alignment on different time series. It reads 6 of the original 28 data files containing amplitude val…
    holgersc > Public > 01_Preprocessing_Time_Alignment_and_Visualization
    0
  17. 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
  18. Workflow
    Keras Autoencoder for Fraud Detection - Training
    Autoencoder Keras Neural network
    +13
    Exercise of the L4-DL Introduction to Deep Learning Course. The goal of this exercise is to train an autoencoder model to detect …
    knime > Education > Courses > L4-DL Introduction to Deep Learning > Session2 > Solutions > 01_Fraud_Detection_Training_Solution
    0
  19. Workflow
    Preprocessing,Time Alignment and Visualization
    Anomaly detection Time series analysis Time alignment
    +6
    This workflow preprocesses and visualizes sensor data for anomaly detection: - Read FFT preprocessed data files with date, time, …
    knime > Codeless Time Series Analysis with KNIME > Chapter 11 > 01_Preprocessing_Time_Alignment_and_Visualization
    0
  20. Workflow
    Time Series AR Visualization
    Anomaly detection Time series analysis Auto-regressive models
    +4
    This workflow visualizes the performance of previously trained auto-regressive models for anomaly detection: - Filter the data to…
    knime > Codeless Time Series Analysis with KNIME > Chapter 11 > 03b_Time_Series_AR_Visualization
    0