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CUSUM 0.1.0 documentation
CUSUM 0.1.0 documentation

User Documentation

  • CUSUM Project
  • Getting Started with CUSUM
  • Usage
  • Get the Code

Technical Documentation

  • Data Generators
    • Change Point Generator
    • Data Streams Generator
  • CUSUM Detectors
    • Cusum Algorithms
      • Vanilla CUSUM Detector Class
      • Examples
      • Page-Hinkley Test Detector Class
      • Examples
      • Probabilistic CUSUM Detector Class
      • Examples
      • Chart CUSUM Detector
      • Examples
      • KS-CUM Detector Class
      • Examples
      • PC1 CUSUM Detector
      • Example Usage
  • ML Model
    • Naive Models
      • Persistent Model
    • Instance-based Learning Models
      • RLS Learning Model
      • SGD Learning Model
      • RLS-CUSUM
      • SGD-CUSUM
    • Lazy Learning Models
    • Batch-based Learning Models
  • Recursive Filters
    • Recursive Average Filter
    • Low Pass Filter
    • Rolling Average Filter
  • Alerting Rules
    • Majority Vote Alerting

Project Information

  • Contributions
  • FAQ
  • References
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ML ModelΒΆ

This module contains the learning models implemented in the CUSUM project. The learning models are responsible for making predictions based on the observed data and updating their internal state as new data is received.

  • Naive Models
  • Instance-based Learning Models
  • Lazy Learning Models
  • Batch-based Learning Models
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Naive Models
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PC1 CUSUM Detector
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