Conditional validation selection

ConditionalValidationSelection

ConditionalValidationSelection(
    validation_set_id: str,
    thresholds: list[float],
    chances: list[float],
    rapid_counts: list[int],
    dimension: Optional[str] = None,
)

Bases: RapidataSelection

Conditional validation selection class.

Probabilistically decides how many validation rapids you want to show per session based on the user score.

Parameters:

Name	Type	Description	Default
validation_set_id	str	The id of the validation set to be used.	required
thresholds	list[float]	The thresholds to use for the user score.	required
chances	list[float]	The chances of showing a validation rapid for each threshold.	required
rapid_counts	list[int]	The amount of validation rapids that will be shown per session of this validation set for each threshold if selected by probability. (all or nothing)	required
dimension	Optional[str]	The dimension of the userScore that will be used in the thresholds. Defaults to None.	None

Example

ConditionalValidationSelection(
    validation_set_id="validation_set_id",
    thresholds=[0, 0.7], # (0 must be the first threshold)
    chances=[1, 0.2],
    rapid_counts=[1, 1]
)

This means that there's a 100% chance of showing a validation rapid if the user score is between 0 and 0.7, and a 20% chance of showing a validation rapid if the user score is between 0.7 and 1.

Source code in src/rapidata/rapidata_client/selection/conditional_validation_selection.py

def __init__(
    self,
    validation_set_id: str,
    thresholds: list[float],
    chances: list[float],
    rapid_counts: list[int],
    dimension: Optional[str] = None,
):
    if len(thresholds) != len(chances) or len(thresholds) != len(rapid_counts):
        raise ValueError(
            "The lengths of thresholds, chances and rapid_counts must be equal."
        )

    self.validation_set_id = validation_set_id
    self.thresholds = thresholds
    self.chances = chances
    self.rapid_counts = rapid_counts
    self.dimension = dimension