6.1. Online-adaptive data stream processing (OADSP)

This sub-framework of MLPro-OA is directly related to the research topic of online machine learning (OML). It deals with online-adaptive stream tasks embedded in a stream workflow as part of an extended process model. This process model extends the non-adaptive DSP process model of sub-framework MLPro-BF-Streams by advanced adaptation mechanisms like

• Event-oriented adaptation

• Cascaded adaptation

• Reverse adaptation

which are explained in more detail below.

The description is still under contruction but parts of the sub-menu and first howtos and API specifications are already available. Browse the menu and see Section ‘Cross reference’ for further details.

Learn more

• 6.1.1. Overview
  • 6.1.1.1. Online-adaptive stream tasks
  • 6.1.1.2. Online-adaptive stream workflows
• 6.1.2. Preprocessing
  • 6.1.2.1. Boundary detection
  • 6.1.2.2. Normalization
    • 6.1.2.2.1. MinMax-Normalization
    • 6.1.2.2.2. Z-Scaling
• 6.1.3. Cluster analysis
• 6.1.4. Change detection
  • 6.1.4.1. Anomaly detection
  • 6.1.4.2. Drift detection
• 6.1.5. Helpers
  • 6.1.5.1. Observer for online-adaptations
  • 6.1.5.2. Observer for change events

Cross reference

• Howtos MPro-OA-Streams

• API reference: MLPro-OA-Streams

• Basics of data stream processing in MLPro