MLPro-Int-scikit-learn - Integration of scikit-learn into MLPro

Welcome to MLPro-Int-scikit-learn, an extension to MLPro to integrate the scikit-learn package. MLPro is a middleware framework for standardized machine learning in Python. It is developed by the South Westphalia University of Applied Sciences, Germany, and provides standards, templates, and processes for hybrid machine learning applications. Scikit-learn, in turn, provides numerous state-of-the-art algorithms for a vast amount of machine learning topics.

MLPro-Int-scikit-learn provides wrapper classes that enable the use of scikit-learn algorithms and data streams in your MLPro applications. The use of these wrappers is illustrated in various example programs.

Preparation

Before running the examples, please install the latest versions of MLPro, scikit-learn, and MLPro-Int-scikit-learn as follows:

pip install mlpro-int-scikit-learn[full] --upgrade

See also

• MLPro - Machine Learning Professional

• MLPro-OA - Sub-framework for online machine learning

• scikit-learn - Machine Learning in Python

• Further MLPro extensions

• MLPro-Int-scikit-learn on GitHub

Example Pool

• Reuse of scikit-learn Data Streams
  • Howto BF-STREAMS-001: Accessing Data Streams From scikit-learn
• Reuse of scikit-learn Anomaly Detectors
  • Howto OA-AD-002: Anomaly Detection using Local Outlier Factor
  • Howto OA-AD-003: Anomaly Detection using Isolation Forest

API Reference

• Wrapper Root Class
  • WrapperSklearn
• Wrappers for scikit-learn Data Streams
  • WrStreamProviderSklearn
  • WrStreamSklearn
• Wrappers for scikit-learn Anomaly Detectors

About

• Release Notes
• Disclaimer
  • Disclaimers for MLPro Usage
  • Consent