def build_vectorization_pipeline(
self) -> Tuple[List[Tuple[str, Any]], Callable[[], List[str]]]:
vect_cur = CountVectorizer(strip_accents='unicode',
analyzer='word',
stop_words='english',
tokenizer=vectorizers.whole_value_as_token)
vect_amount = vectorizers.NumberVectorizer()
def get_feature_names_(vect_cur_, vect_amount_):
def res():
return ['currency_' + str(c) for c in vect_cur_.get_feature_names()] \
+ ['amount_' + str(fn) for fn in vect_amount_.get_feature_names()]
return res
return [
('vect',
FeatureUnion(transformer_list=[(
'currency',
Pipeline([
('selector',
vectorizers.DictItemSelector(item='currency')),
('clean', vectorizers.ReplaceNoneTransformer('')),
('vect', vect_cur),
('tfidf', TfidfTransformer()),
])),
('amount',
Pipeline([
('selector',
vectorizers.DictItemSelector(
item='amount')),
('vect', vect_amount),
]))]))
], get_feature_names_(vect_cur, vect_amount)
def build_vectorization_pipeline(self) -> List[Tuple[str, Any]]:
return [
('vect', FeatureUnion(transformer_list=[
('currency', Pipeline([
('selector', vectorizers.DictItemSelector(item='currency')),
('clean', vectorizers.ReplaceNoneTransformer('')),
('vect', CountVectorizer(strip_accents='unicode', analyzer='word',
stop_words='english', tokenizer=vectorizers.whole_value_as_token)),
('tfidf', TfidfTransformer()),
])),
('amount', Pipeline([
('selector', vectorizers.DictItemSelector(item='amount')),
('vect', vectorizers.NumberVectorizer()),
]))
]))
]
def build_vectorization_pipeline(
self) -> Tuple[List[Tuple[str, Any]], Callable[[], List[str]]]:
vect = vectorizers.NumberVectorizer(
to_float_converter=lambda d: d.total_seconds() if d else 0
if d else 0)
return [('vect', vect)], self._wrap_get_feature_names(vect)
def build_vectorization_pipeline(
self) -> Tuple[List[Tuple[str, Any]], Callable[[], List[str]]]:
vect = vectorizers.NumberVectorizer()
return [('vect', vect)], self._wrap_get_feature_names(vect)
def build_vectorization_pipeline(self) -> List[Tuple[str, Any]]:
return [('vect', vectorizers.NumberVectorizer())]
def build_vectorization_pipeline(self) -> List[Tuple[str, Any]]:
return [('vect',
vectorizers.NumberVectorizer(to_float_converter=lambda d: d.total_seconds() if d else 0 if d else 0))]
