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explicitly assign arguments to avoid incorrect argument assignments #389

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merged 1 commit into from
Oct 22, 2024
Merged

explicitly assign arguments to avoid incorrect argument assignments #389

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10 changes: 6 additions & 4 deletions libmultilabel/linear/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,17 +76,18 @@ class MultiLabelEstimator(sklearn.base.BaseEstimator):
scoring_metric (str, optional): The scoring metric. Defaults to 'P@1'.
"""

def __init__(self, options: str = "", linear_technique: str = "1vsrest", scoring_metric: str = "P@1"):
def __init__(self, options: str = "", linear_technique: str = "1vsrest", scoring_metric: str = "P@1", multiclass: bool = False):
super().__init__()
self.options = options
self.linear_technique = linear_technique
self.scoring_metric = scoring_metric
self._is_fitted = False
self.multiclass = multiclass

def fit(self, X: sparse.csr_matrix, y: sparse.csr_matrix):
X, y = sklearn.utils.validation.check_X_y(X, y, accept_sparse=True, multi_output=True)
self._is_fitted = True
self.model = LINEAR_TECHNIQUES[self.linear_technique](y, X, self.options)
self.model = LINEAR_TECHNIQUES[self.linear_technique](y, X, options=self.options)
return self

def predict(self, X: sparse.csr_matrix) -> np.ndarray:
Expand All @@ -96,8 +97,9 @@ def predict(self, X: sparse.csr_matrix) -> np.ndarray:

def score(self, X: sparse.csr_matrix, y: sparse.csr_matrix) -> float:
metrics = linear.get_metrics(
[self.scoring_metric],
y.shape[1],
monitor_metrics=[self.scoring_metric],
num_classes=y.shape[1],
multiclass=self.multiclass
)
preds = self.predict(X)
metrics.update(preds, y.toarray())
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6 changes: 3 additions & 3 deletions linear_trainer.py
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Expand Up @@ -51,9 +51,9 @@ def linear_train(datasets, config):
model = LINEAR_TECHNIQUES[config.linear_technique](
datasets["train"]["y"],
datasets["train"]["x"],
config.liblinear_options,
config.tree_degree,
config.tree_max_depth,
options=config.liblinear_options,
K=config.tree_degree,
dmax=config.tree_max_depth,
)
else:
model = LINEAR_TECHNIQUES[config.linear_technique](
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