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  • 03_Keras_Autoencoder_for_Fraud_Detection_Training
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Keras Autoencoder for Fraud Detection Training

autoencoder Keras neural network backpropagation deep learning +13

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Partition numeric input data into a training, test, and validation set. Normalize the data into range [0,1]. Build a Keras autoencoder to reconstruct the input data without anomalies (fraudulent transactions). Apply the Keras model to the test set with anomalies. Detect anomalies in the test set as exceptional high reconstruction errors. Find the optimal threshold for the reconstruction error and evaluate the model performance by producing the accuracy statistics of the model.

Used extensions & nodes

Created with KNIME Analytics Platform version 4.3.0
  • KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • KNIME Deep Learning - Keras Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • KNIME Expressions Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • KNIME JavaScript Views (Labs) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • KNIME Math Expression (JEP) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • KNIME Optimization extension Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

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