Training architecture

The training architecture is used to construct a classifier from examples and background knowledge. In figure 5.1, ovals represent inputs and outputs, and rectangles represent processes on data.

• Raw training data
• Parametrised event primitives
  • Example PEP: A ``straight-line'' approximation for continuous-valued channels
  • Example PEP: ``Delta'' detection for discrete-valued attributes
• Event extraction
• Global features
  • Example global attributes
• Parameter clustering
• Event attribution
• Recombination
• Feature selection
• Conventional attribute-value learning
• Classifier