信用违约损失模型
信用违约损失模型：构建并训练 LGD（违约损失率）机器学习模型，支持基于历史违约数据的信用风险量化评估与预测。 含 14 条反模式约束。
晶体简介
Constraints
Evidence Quality
Medium confidence — review before critical use
31 条不可违反的约束
WHENWhen implementing data acquisition for LGD regression model
ACTIONReturn a DataFrame containing exactly 'X' and 'Y' columns
CONSEQUENCEThe downstream lgdModel.py module accesses df[['X']] and df['Y'] columns without validation, causing KeyError exceptions if column names are different
WHENWhen implementing local file mode (choice=1) in dataSource
ACTIONRead CSV file from server_dirs/{server_id}/regression_data.csv path
CONSEQUENCEpandas.read_csv will raise FileNotFoundError if the file path is incorrect, and there is no try-except handler to provide meaningful error messages
WHENWhen configuring data transport for the LGD model
ACTIONPass choice values other than 1 or 2 to dataSource
CONSEQUENCEIf choice is neither 1 nor 2, the function returns None implicitly, causing lgdModel.py to fail when trying to access df[['X']] columns
常见问题
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