This program demonstrates the use of Learning Entropy for novelty detection in time series where relatively simple real-time learning systems can instantly detect novelty in otherwise complex dynamical behaviour.

This program and the Python code is free for non-commercial use with no warranty.

Updates:
v. 1.3: Inverse z-scoring bug fixed. Unused function get_path deleted.
v. 1.2: Single-hidden layer MLP predictor implemented. Prediction horizon p - functionality fixed.
v. 1.1: "Separate Figure" button and functionality was added.

Project Samples

Learning Entropy (Demo) Module Screenshot 1

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License

MIT License

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Registered

2014-06-30
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