[2026-05-28] 외부 데이터 학습 파이프라인 복구
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+13
-1
@@ -15,16 +15,24 @@ EXCLUDED_COLUMNS = {
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"name",
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"entry_time",
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"exit_time",
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"exit_price",
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"sample_time",
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"created_at",
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"exit_reason",
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"strategy",
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"reason",
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"pnl",
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"source_file",
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"ai_win_score",
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"ai_stop_loss_score",
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"ai_model_version",
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}
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EXCLUDED_PREFIXES = (
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"price_",
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"ret_",
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"mfe_",
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"mae_",
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)
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def select_feature_columns(df: pd.DataFrame, targets: Iterable[str] = LABEL_COLUMNS) -> list[str]:
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@@ -32,7 +40,11 @@ def select_feature_columns(df: pd.DataFrame, targets: Iterable[str] = LABEL_COLU
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numeric_columns = [
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column
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for column in df.columns
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if column not in excluded and pd.api.types.is_numeric_dtype(df[column])
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if (
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column not in excluded
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and not column.startswith(EXCLUDED_PREFIXES)
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and pd.api.types.is_numeric_dtype(df[column])
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)
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]
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return sorted(numeric_columns)
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