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Add statistics attribute to slicefinder #40

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Apr 6, 2023
Merged

Add statistics attribute to slicefinder #40

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4001023
Add statistics attribute to slicefinder
adedaran Apr 5, 2023
911639f
Complete docstring
adedaran Apr 5, 2023
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36 changes: 35 additions & 1 deletion sliceline/slicefinder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -70,6 +70,15 @@ class Slicefinder(BaseEstimator, TransformerMixin):
average_error_: float
Mean value of the input error.

top_slices_statistics_: list of dict of length `len(top_slices_)`
The statistics of the slices found sorted by slice's scores.
For each slice, the following statistics are stored:
- slice_score: the score of the slice (defined in `_score` method)
- sum_slice_error: the sum of all the errors in the slice
- max_slice_error: the maximum of all errors in the slice
- slice_size: the number of elements in the slice
- slice_average_error: the average error in the slice (sum_slice_error / slice_size)

References
----------
`SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging
Expand All @@ -92,7 +101,8 @@ def __init__(
self.verbose = verbose

self._one_hot_encoder = self._top_slices_enc = None
self.top_slices_ = self.average_error_ = None
self.top_slices_ = self.top_slices_statistics_ = None
self.average_error_ = None

if self.verbose:
logger.setLevel(logging.DEBUG)
Expand Down Expand Up @@ -679,4 +689,28 @@ def _search_slices(
top_k_slices
)

# compute slices' average errors
top_k_statistics = np.column_stack(
(
top_k_statistics,
np.divide(top_k_statistics[:, 1], top_k_statistics[:, 3]),
)
)

# transform statistics to a list of dict
statistics_names = [
"slice_score",
"sum_slice_error",
"max_slice_error",
"slice_size",
"slice_average_error",
]
self.top_slices_statistics_ = [
{
stat_name: stat_value
for stat_value, stat_name in zip(statistic, statistics_names)
}
for statistic in top_k_statistics
]

logger.debug("Terminated at level %i." % level)
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