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libmultilabel/linear/linear.py

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@@ -546,7 +546,7 @@ def get_topk_labels(label_mapping: np.ndarray, preds: np.ndarray, top_k: int = 5
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"""Get top k predictions from decision values.
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Args:
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label_mapping (np.ndarray): A ndarray of class labels that maps each label to its index.
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label_mapping (np.ndarray): A ndarray of class labels that maps each index (from 0 to ``num_class-1``) to its label.
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preds (np.ndarray): A matrix of decision values with dimension number of instances * number of classes.
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top_k (int): Determine how many classes per instance should be predicted.
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