Asserts the validity of the function with all valid types We want to make sure that `subsample` works correctly with all the types listed as

Makes sure we raise a proper message to the user, when providing not supported data input

Expects ------- * Should be able to load each of the targets

Check if we can fit in a given type (numpy) yet transform if the user changes the type (pandas then) This is problematic only in the cas

Test that the encoding/decoding works in 1D

Makes sure we raise a proper message to the user, when providing not supported data input

Expects ------- * A UserDask should not close the client after exiting context

Expects ------- * Should be able to correctly consider valid run dir names

Parameters ---------- bad_arg: Any An arg which is not a Mapping Expects ------- * Should raise a ValueError

Parameters ---------- key: str A key which should not be in the parameters Expects ------- * Should raise a ValueErr

Parameters ---------- memory_allocation: Any A bad float value for memory_allocation Expects ------- * Should raise

Parameters ---------- memory_allocation: int A bad float int for memory_allocation memory_limit: int The memory limi

Parameters ---------- memory_allocation: Any A bad type for memory_allocation Expects ------- * Should raise a Value

Parameters ---------- methods: int A bad type for key methods Expects ------- * Should raise a ValueError

Parameters ---------- methods: int A bad type for key methods Expects ------- * Should raise a ValueError

Parameters ---------- arg: Dict[str, any] Expects ------- * Should validate without error * Should return a dict identic

Parameters ---------- memory_allocation: Union[float, int] A valid memory_allocation Expects ------- * Should valida

Parameters ---------- methods: List[str] A valid list of methods Expects ------- * Should validate without error

Makes sure we raise a proper message to the user, when providing not supported data input

Expects ------- * Should properly indicate when a file was modified

Expects ------- * Should be able to build a valid ensemble with different combinations of metrics * Should produce a validation score

Fixtures -------- tmp_path : Path Built in pytest fixture Returns ------- str The directory as a str

The transform function calls the transform function of the underlying scikit-learn model and returns the transformed array. Parameter