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Made categorical dictionary more cohesive to overall structure #1454

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Merged
mfeurer merged 11 commits into from
May 9, 2022
Merged

Made categorical dictionary more cohesive to overall structure #1454

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8d47cc9
change treatment of string features. In file `smbo.py` string columns…
Louquinze Mar 24, 2022
9263e85
change treatment of string features. In file `smbo.py` string columns…
Louquinze Mar 24, 2022
9836f99
Merge remote-tracking branch 'origin/development' into development
Louquinze May 2, 2022
b9da740
made categorical dictionary more cohesive. Use the previously create …
Louquinze May 2, 2022
230bed7
change test files since they now get the feat type dictionary and no …
Louquinze May 2, 2022
ed79585
change test files since they now get the feat type dictionary and no …
Louquinze May 3, 2022
b2dea63
moved feat_type to categorical conv. to the helper functions
Louquinze May 4, 2022
893d8ff
fixed minor issues
Louquinze May 5, 2022
15cec29
fixed minor issues
Louquinze May 6, 2022
b299111
fixed minor issues
Louquinze May 9, 2022
fc9628d
fixed bug in metalearning tests
Louquinze May 9, 2022
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13 changes: 6 additions & 7 deletions autosklearn/metalearning/metafeatures/metafeature.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,19 +15,18 @@ def __init__(self):
pass

@abstractmethod
def _calculate(cls, X, y, logger, categorical):
def _calculate(cls, X, y, logger, feat_type):
pass

def __call__(self, X, y, logger, categorical=None):
if categorical is None:
categorical = [False for i in range(X.shape[1])]
def __call__(self, X, y, logger, feat_type=None):
if feat_type is None:
feat_type = {i: "numerical" for i in range(X.shape[1])}
starttime = time.time()

try:
if scipy.sparse.issparse(X) and hasattr(self, "_calculate_sparse"):
value = self._calculate_sparse(X, y, logger, categorical)
value = self._calculate_sparse(X, y, logger, feat_type)
else:
value = self._calculate(X, y, logger, categorical)
value = self._calculate(X, y, logger, feat_type)
comment = ""
except MemoryError:
value = None
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