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[Refactor] faster get_leafs method for xbooster/lgb_constructor.py #13

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[Refactor] faster get_leafs method for xbooster/lgb_constructor.py #13

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9 changes: 4 additions & 5 deletions xbooster/lgb_constructor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -190,13 +190,12 @@ def get_leafs(

# For margin output, get raw scores per tree
# Each tree's prediction is returned as-is (no base_score adjustment needed)
df_leafs = pd.DataFrame()

tree_results = []
for i in range(n_trees):
df_leafs[f"tree_{i}"] = self.model.predict(
X, raw_score=True, start_iteration=i, num_iteration=1
)
res = self.model.predict(X, raw_score=True, start_iteration=i, num_iteration=1)
tree_results.append(res)

df_leafs = pd.DataFrame(np.column_stack(tree_results), index=X.index, columns=_colnames)
return df_leafs

def extract_leaf_weights(self) -> pd.DataFrame:
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