8000 Explicitly compare given feature list and specified feature list in TableRowClassifier · Issue #19 · haesleinhuepf/apoc · GitHub
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Explicitly compare given feature list and specified feature list in TableRowClassifier #19

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haesleinhuepf opened this issue Mar 28, 2022 · 1 comment
Open

Explicitly compare given feature list and specified feature list in TableRowClassifier #19

haesleinhuepf opened this issue Mar 28, 2022 · 1 comment

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@haesleinhuepf
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I have the suspicion that a TableRowClassifier trained with features "A B C" would also be applicable to a table with columns "E D F". We should check if provided tables contains the right columns.

This issue may be have been introduced with #17
@kevinyamauchi
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I believe we are already do that here:

apoc/apoc/_table_row_classifier.py

Line 117 in f56c5c0

ordered_features = self.order_feature_table(feature_table)

apoc/apoc/_table_row_classifier.py

Lines 165 to 181 in f56c5c0

def order_feature_table(self, feature_table: Dict[str, np.ndarray]) -> List[np.ndarray]:
"""Coerce a feature table into the format required by the classifier.
Parameters
----------
feature_table : Dict[str, Union[List[float], np.ndarray]]
The table from which to make the prediction. Each row of the table
will be classified. The table can either be a pandas DataFrame or a
Dict with string keys (column names) and numpy array columns.
Returns
-------
ordered_features : List[np.ndarray]
The features stored in a list. The order of the features is
specified by self.ordered_feature_names
"""
return [np.asarray(feature_table[feature]) for feature in self.ordered_feature_names]

This should throw a key error if the the required columns aren't present in the feature table. We should add a test to check though!

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@kevinyamauchi @haesleinhuepf
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