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[Refactor] make faster construct_scorecard method for xbooster/lgb_constructor.py #10

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[Refactor] make faster construct_scorecard method for xbooster/lgb_constructor.py #10

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8e74c5e
make it fast
RektPunk Dec 20, 2025
f83aadb
clarify variable name
RektPunk Dec 20, 2025
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41 changes: 16 additions & 25 deletions xbooster/lgb_constructor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -293,36 +293,27 @@ def construct_scorecard(self) -> pd.DataFrame:
f"Invalid leaf index shape {tree_leaf_idx.shape}. Expected {(len(labels), n_trees)}"
)

df_binning_table = pd.DataFrame()
for i in range(n_trees):
index_and_label = pd.concat(
[
pd.Series(tree_leaf_idx[:, i], name="leaf_idx"),
pd.Series(labels, name="label"),
],
axis=1,
)
# Create a binning table
binning_table = (
index_and_label.groupby("leaf_idx").agg(["sum", "count"]).reset_index()
).astype(float)
binning_table.columns = ["leaf_idx", "Events", "Count"] # type: ignore
binning_table["tree"] = i
binning_table["NonEvents"] = binning_table["Count"] - binning_table["Events"]
binning_table["EventRate"] = binning_table["Events"] / binning_table["Count"]
binning_table = binning_table[
["tree", "leaf_idx", "Events", "NonEvents", "Count", "EventRate"]
]
# Aggregate indices, leafs, and counts of events and non-events
df_binning_table = pd.concat([df_binning_table, binning_table], axis=0)
# Aggregate indices, leafs, and counts of events and non-events
tree_leaf_idx_long = pd.DataFrame(tree_leaf_idx).melt(var_name="Tree", value_name="Node")
tree_leaf_idx_long["label"] = np.tile(labels.values, tree_leaf_idx.shape[1])
binning_table = (
tree_leaf_idx_long.groupby(["Tree", "Node"])["label"]
.agg(["sum", "count"])
.reset_index()
)
binning_table.columns = ["Tree", "Node", "Events", "Count"]
df_binning_table = binning_table.assign(
NonEvents=lambda df: df["Count"] - df["Events"],
EventRate=lambda df: df["Events"] / df["Count"],
)[["Tree", "Node", "Events", "NonEvents", "Count", "EventRate"]]

# Extract leaf weights (XAddEvidence)
df_x_add_evidence = self.extract_leaf_weights()
self.lgb_scorecard = df_x_add_evidence.merge(
df_binning_table,
left_on=["Tree", "Node"],
right_on=["tree", "leaf_idx"],
on=["Tree", "Node"],
how="left",
).drop(["tree", "leaf_idx"], axis=1)
)

self.lgb_scorecard = self.lgb_scorecard[
[
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