• Corpus ID: 14995779

Probabilistic Graphical Models - Principles and Techniques

@inproceedings{Koller2009ProbabilisticGM,
  title={Probabilistic Graphical Models - Principles and Techniques},
  author={Daphne Koller and Nir Friedman},
  year={2009}
}
Most tasks require a person or an automated system to reason -- to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is… 
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References

Introduction discussion of some of these alternative frameworks see Shafer and Pearl
  • Introduction discussion of some of these alternative frameworks see Shafer and Pearl
  • 1988