MedianAbsoluteError

from tmlt.tune import MedianAbsoluteError

class tmlt.tune.MedianAbsoluteError(measure_column, join_columns, grouping_columns=None, *, name=None, description=None, baseline=None, output=None)

Bases: QuantileAbsoluteError

Computes the median absolute error.

Equivalent to QuantileAbsoluteError with quantile = 0.5.

Example

>>> dp_outputs = {"O": dp_df}
>>> baseline_df = spark.createDataFrame(
...     pd.DataFrame(
...         {
...             "A": ["a1", "a2", "a3"],
...             "X": [100, 100, 100]
...         }
...     )
... )
>>> baseline_outputs = {"default": {"O": baseline_df}}

>>> metric = MedianAbsoluteError(
...     measure_column="X",
...     join_columns=["A"]
... )
>>> metric.quantile
0.5
>>> metric.join_columns
['A']
>>> result = metric(dp_outputs, baseline_outputs).value
>>> result
10