All Projects → Vicam → Unsupervised_anomaly_detection

Vicam / Unsupervised_anomaly_detection

A Notebook where I implement differents anomaly detection algorithms on a simple exemple. The goal was just to understand how the different algorithms works and their differents caracteristics.

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Unsupervised Anomaly Detection

Motivation

A Notebook where I implement differents Unsupervised anomaly detection algorithms on a simple exemple. The goal was to understand how the different algorithms works and their differents caracteristics. I have created this notebook after reading this article: https://iwringer.wordpress.com/2015/11/17/anomaly-detection-concepts-and-techniques/ I implement the algorithms cited in the article and add some.

Algorithm implemented :

  • Cluster based anomaly detection (K-mean)
  • Repartition of data into categories then Gaussian/Elliptic Enveloppe on each categories separately
  • Markov Chain
  • Isolation Forest
  • One class SVM
  • RNN (comparison between prediction and reality)
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