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.
License
MIT LicenseFollow Learning Entropy (Demo) Module
Other Useful Business Software
Stop vibe-debugging.
AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of Learning Entropy (Demo) Module!