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

Project Activity

See All Activity >

License

MIT License

Follow Learning Entropy (Demo) Module

Learning Entropy (Demo) Module Web Site

You Might Also Like
Cybersecurity Management Software for MSPs Icon
Cybersecurity Management Software for MSPs

Secure your clients from cyber threats.

Define and Deliver Comprehensive Cybersecurity Services. Security threats continue to grow, and your clients are most likely at risk. Small- to medium-sized businesses (SMBs) are targeted by 64% of all cyberattacks, and 62% of them admit lacking in-house expertise to deal with security issues. Now technology solution providers (TSPs) are a prime target. Enter ConnectWise Cybersecurity Management (formerly ConnectWise Fortify) — the advanced cybersecurity solution you need to deliver the managed detection and response protection your clients require. Whether you’re talking to prospects or clients, we provide you with the right insights and data to support your cybersecurity conversation. From client-facing reports to technical guidance, we reduce the noise by guiding you through what’s really needed to demonstrate the value of enhanced strategy.
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of Learning Entropy (Demo) Module!

Additional Project Details

Registered

2014-06-30