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Update Bayesian Binary Sensor configuration (#6998)
* Update Bayesian Binary Sensor configuration * Clarify observation platform example differences * Update binary_sensor.bayesian.markdown
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@ -14,7 +14,6 @@ ha_release: 0.53
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ha_qa_scale: internal
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---
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The `bayesian` binary sensor platform observes the state from multiple sensors and uses [Bayes' rule](https://en.wikipedia.org/wiki/Bayes%27_theorem) to estimate the probability that an event has occurred given the state of the observed sensors. If the estimated posterior probability is above the `probability_threshold`, the sensor is `on` otherwise it is `off`.
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This allows for the detection of complex events that may not be readily observable, e.g., cooking, showering, in bed, the start of a morning routine, etc. It can also be used to gain greater confidence about events that _are_ directly observable, but for which the sensors can be unreliable, e.g., presence.
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@ -36,20 +35,58 @@ binary_sensor:
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to_state: 'on'
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```
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Configuration variables:
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- **prior** (*Required*): The prior probability of the event. At any point in time (ignoring all external influences) how likely is this event to occur?
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- **probability_threshold** (*Optional*): The probability at which the sensor should trigger to `on`.
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- **name** (*Optional*): Name of the sensor to use in the frontend. Defaults to `Bayesian Binary sensor`.
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- **observations** array (*Required*): The observations which should influence the likelihood that the given event has occurred.
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- **entity_id** (*Required*): Name of the entity to monitor.
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- **prob_given_true** (*Required*): The probability of the observation occurring, given the event is `true`.
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- **prob_given_false** (*Optional*): The probability of the observation occurring, given the event is `false` can be set as well. If `prob_given_false` is not set, it will default to `1 - prob_given_true`.
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- **platform** (*Required*): The only supported observation platforms are `state` and `numeric_state`, which are modeled after their corresponding triggers for automations, requiring `below` and/or `above` instead of `to_state`.
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- **to_state** (*Required*): The target state.
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{% configuration %}
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prior:
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description: >
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The prior probability of the event. At any point in time
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(ignoring all external influences) how likely is this event to occur?
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required: true
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type: float
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probability_threshold:
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description: The probability at which the sensor should trigger to `on`.
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required: false
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type: float
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default: 0.5
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name:
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description: Name of the sensor to use in the frontend.
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required: false
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type: string
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default: Bayesian Binary Sensor
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observations:
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description: The observations which should influence the likelihood that the given event has occurred.
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required: true
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type: list
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keys:
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entity_id:
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description: Name of the entity to monitor.
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required: true
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type: string
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prob_given_true:
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description: The probability of the observation occurring, given the event is `true`.
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required: true
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type: float
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prob_given_false:
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description: The probability of the observation occurring, given the event is `false` can be set as well.
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required: false
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type: float
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default: "`1 - prob_given_true` if `prob_given_false` is not set"
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platform:
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description: >
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The only supported observation platforms are `state` and `numeric_state`,
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which are modeled after their corresponding triggers for automations,
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requiring `below` and/or `above` instead of `to_state`.
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required: true
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type: string
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to_state:
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description: The target state.
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required: true
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type: string
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{% endconfiguration %}
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## {% linkable_title Full examples %}
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The following is an example for the `state` observation platform.
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```yaml
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# Example configuration.yaml entry
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binary_sensor:
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@ -78,6 +115,8 @@ binary_sensor:
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to_state: 'below_horizon'
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```
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Next up an example which targets the `numeric_state` observation platform,
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as seen in the configuration it requires `below` and/or `above` instead of `to_state`.
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```yaml
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# Example configuration.yaml entry
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