/Anomaly-Detection

Anomaly detection methods and implementation

Primary LanguageJupyter Notebook

Anomaly-Detection

Anomaly detection methods and implementation.

Preprocessing

  • utils.py - Trajectory matrix/ rolling window representation of time series data.

Algorithms

  • LSTM Autoencoder
    • Long short-term memory (LSTM) is a recurrent neural network (RNN) architecture, used to process entire sequences of data.
    • An autoencoder learns a representation for a set of data in an unsupervised manner by training the network to ignore signal “noise”.
    • The reconstruction error serves as an indicator to the extent of a data instance being an anomaly.

Datasets

  • Numenta Anomaly Benchmark
    • machine_temperature_system_failure.csv
      • Temperature sensor data of an internal component of a large, industrial machine.
      • The first anomaly is a planned shutdown of the machine.
      • The second anomaly is difficult to detect and directly led to the third anomaly, a catastrophic failure of the machine.