Skip to main content

Event Correlation and Changing Detection Algorithm

Project description

scikit-event-correlation

Build PyPi
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

  1. Install with pip:
python -m pip install scikit-event-correlation

Example Project

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

scikit-event-correlation-1.0.2.tar.gz (4.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

scikit_event_correlation-1.0.2-py3-none-any.whl (5.3 kB view details)

Uploaded Python 3

File details

Details for the file scikit-event-correlation-1.0.2.tar.gz.

File metadata

  • Download URL: scikit-event-correlation-1.0.2.tar.gz
  • Upload date:
  • Size: 4.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.1

File hashes

Hashes for scikit-event-correlation-1.0.2.tar.gz
Algorithm Hash digest
SHA256 fa472dbc18d00c37ade832b8743fe2f52052522b335772ea8c78bd059350744d
MD5 3e46b1cf9987213f4e75611428ff6945
BLAKE2b-256 facdc7a361023117002a328d94de916ad98b83f17fa98fea4ed7923a1cf6e240

See more details on using hashes here.

File details

Details for the file scikit_event_correlation-1.0.2-py3-none-any.whl.

File metadata

  • Download URL: scikit_event_correlation-1.0.2-py3-none-any.whl
  • Upload date:
  • Size: 5.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.1

File hashes

Hashes for scikit_event_correlation-1.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 8d28b9b8b3618338292cfc43be6e3b1d76d11d88c771ebd9170ec0df2baa0ab9
MD5 dec638fda6f0ca3feda988b38553d3c9
BLAKE2b-256 c13bb345431ce3e102f971bf15f9b931fc388d6870616f4b54b2429c16706ed6

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page