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Bayesian network on fire alarm system

Source: R/fire_alarm.R
fire_alarm.Rd

fire_alarm is a bn.fit object including a Bayesian network for a fire alarm system.

Usage

fire_alarm

Format

The Bayesian network fire_alarm includes the following nodes:

  • Fire: two-level factor with levels TRUE and FALSE. It indicates presence or absence of a fire.

  • Smoke: two level-factor with levels TRUE and FALSE. It indicates presence or absence of smoke.

  • Alarm: three level-factor with levels TRUE, MALFUNCTION and FALSE. It indicates if the alarm is ringing, malfunctioning or not ringing.

  • Tampering: two level-factor with levels TRUE and FALSE. It indicates if the alarm system has been tampered or not.

  • Leaving: two level-factor with levels TRUE and FALSE. It indicates if the building is being evacuated or not.

  • Report: two level-factor with levels TRUE and FALSE. It indicates if the incident has been reported or not.

Source

Hei Chan, Adnan Darwiche (2002). "When do numbers really matter?". Journal of Artificial Intelligence Research 17 (265-287).