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Printer Nightmare Belief Network from D. Barber "Bayesian Reasoning and Machine Learning"

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PrinterNightmare

Printer Nightmare Belief Network from D. Barber "Bayesian Reasoning and Machine Learning"

The demo shows how to:

  1. Learn model parameters from data (issue and component state history)
  2. Query trained model

The model is trained from 15 visits of a repairmen to CheapCo. The query infers the probability of Fuse Assembly fault given that Burning smell and Paper Jam is observed (no other issues).

Updated to use open source Infer.NET.

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Printer Nightmare Belief Network from D. Barber "Bayesian Reasoning and Machine Learning"

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