Scikit-event-correlation - Event Correlation and Forecasting over High Dimensional Streaming Sensor Data algorithms

Last update: Oct 30, 2022

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Overview

scikit-event-correlation

Event Correlation and Changing Detection Algorithm

Theory

Correlating events in complex and dynamic IoT environments is a challenging task not only because of the amount of available data that needs to be processed but also due to the call for time efficient data processing. We propose the adoption of a univariate change detection algorithm for real-time event detection and we implement a stepwise event correlation scheme based on a first-order Markov model.

Requirements

Python 3.6 to 3.10 supported.
scikit-learn 1.0.0 to 1.02 supported.

Installation

Install with pip:

python -m pip install scikit-event-correlation

Example Project

See the example project in the example/ directory of the GitHub repository.

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Releases(v1.0.1)

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First Release Supported Algorithms CumSum, Stepwise
Source code(tar.gz)
Source code(zip)

Owner

Intellia ICT

Intellia is an SME targetting innovation in the areas of Augmented Reality and AI/ML solutions.

GitHub Repository

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Scikit-event-correlation - Event Correlation and Forecasting over High Dimensional Streaming Sensor Data algorithms

Related tags

Overview

scikit-event-correlation

Theory

Requirements

Installation

Example Project

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