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Knowledge Engineering

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Presentation on theme: "Knowledge Engineering"— Presentation transcript:

1 Knowledge Engineering
Representation Probabilistic Graphical Models Wrapup Knowledge Engineering

2 Important Distinctions
Template based versus specific Directed versus undirected Generative versus discriminative Hybrids are also common

3 Important Distinctions
Template-based Specific

4 Important Distinctions
Generative Discriminative

5 Variable Types Target Observed Latent
Including complex, constructed features Latent GMT W1 W2 W3 Wk

6 Structure Causal versus non-causal ordering … … GMT W1 W2 W3 Wk GMT W1

7 Extending the Conversation

8 Parameters: Values What matters: Structured CPDs Zeros
Orders of magnitude Relative values Structured CPDs

9 Parameters: Local Structure
Table CPDs are the exception Context-specific Aggregating Discrete Continuous

10 Iterative Refinement Model testing Sensitivity analysis for parameters
Error analysis Add features Add dependencies

11 END END END


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