evalml.data_checks.InvalidTargetDataCheck.__init__

InvalidTargetDataCheck.__init__(problem_type, objective, n_unique=100)[source]

Check if the target is invalid for the specified problem type.

Parameters

  • problem_type (str or ProblemTypes) – The specific problem type to data check for. e.g. ‘binary’, ‘multiclass’, ‘regression, ‘time series regression’

  • objective (str or ObjectiveBase) – Name or instance of the objective class.

  • n_unique (int) – Number of unique target values to store when problem type is binary and target incorrectly has more than 2 unique values. Non-negative integer. Defaults to 100. If None, stores all unique values.

evalml.data_checks.InvalidTargetDataCheck evalml.data_checks.InvalidTargetDataCheck.validate