{ "case": 2, "report_id": "d73396cc-4ad6-493e-a69a-0cd2a0a435e6", "question": "固定分箱怎样比较五分区与无标签分布？", "consumer": "deterministic public API queries; no LLM", "description": { "report_type": "MarsBinningReport", "report_id": "d73396cc-4ad6-493e-a69a-0cd2a0a435e6", "format_version": 1, "feature_metadata": { "NAME_CONTRACT_TYPE": { "display_name": "贷款合同类型", "description": "Identification if loan is cash or revolving", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "CODE_GENDER": { "display_name": "客户性别", "description": "Gender of the client", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_OWN_CAR": { "display_name": "是否拥有汽车", "description": "Flag if the client owns a car", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_OWN_REALTY": { "display_name": "是否拥有住宅", "description": "Flag if client owns a house or flat", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "CNT_CHILDREN": { "display_name": "子女人数", "description": "Number of children the client has", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "次数或人数（按官方定义）" }, "AMT_INCOME_TOTAL": { "display_name": "客户收入", "description": "Income of the client", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "原始金额单位（币种未公开）" }, "AMT_ANNUITY": { "display_name": "贷款年金", "description": "Loan annuity", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "原始金额单位（币种未公开）" }, "AMT_GOODS_PRICE": { "display_name": "贷款对应商品价格", "description": "For consumer loans it is the price of the goods for which the loan is given", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "原始金额单位（币种未公开）" }, "NAME_TYPE_SUITE": { "display_name": "申请时陪同人员类型", "description": "Who was accompanying client when he was applying for the loan", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "NAME_INCOME_TYPE": { "display_name": "收入类型", "description": "Clients income type (businessman, working, maternity leave,…)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "NAME_EDUCATION_TYPE": { "display_name": "最高教育程度", "description": "Level of highest education the client achieved", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "NAME_FAMILY_STATUS": { "display_name": "家庭状态", "description": "Family status of the client", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "NAME_HOUSING_TYPE": { "display_name": "居住情况", "description": "What is the housing situation of the client (renting, living with parents, ...)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "REGION_POPULATION_RELATIVE": { "display_name": "居住地区归一化人口规模", "description": "Normalized population of region where client lives (higher number means the client lives in more populated region)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "DAYS_BIRTH": { "display_name": "申请时年龄天数（原始值）", "description": "Client's age in days at the time of application", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "天（相对申请日，保留原始符号）" }, "DAYS_EMPLOYED": { "display_name": "开始当前工作相对申请的天数", "description": "How many days before the application the person started current employment", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "天（相对申请日，保留原始符号）" }, "DAYS_REGISTRATION": { "display_name": "变更登记相对申请的天数", "description": "How many days before the application did client change his registration", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "天（相对申请日，保留原始符号）" }, "DAYS_ID_PUBLISH": { "display_name": "变更身份证件相对申请的天数", "description": "How many days before the application did client change the identity document with which he applied for the loan", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "天（相对申请日，保留原始符号）" }, "OWN_CAR_AGE": { "display_name": "汽车年龄", "description": "Age of client's car", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_MOBIL": { "display_name": "是否提供手机号码", "description": "Did client provide mobile phone (1=YES, 0=NO)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_EMP_PHONE": { "display_name": "是否提供工作电话", "description": "Did client provide work phone (1=YES, 0=NO)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_WORK_PHONE": { "display_name": "是否提供家庭电话（官方字段说明）", "description": "Did client provide home phone (1=YES, 0=NO)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_CONT_MOBILE": { "display_name": "手机是否可联系", "description": "Was mobile phone reachable (1=YES, 0=NO)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_PHONE": { "display_name": "是否提供家庭电话", "description": "Did client provide home phone (1=YES, 0=NO)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_EMAIL": { "display_name": "是否提供电子邮箱", "description": "Did client provide email (1=YES, 0=NO)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "OCCUPATION_TYPE": { "display_name": "职业类型", "description": "What kind of occupation does the client have", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "CNT_FAM_MEMBERS": { "display_name": "家庭成员人数", "description": "How many family members does client have", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "次数或人数（按官方定义）" }, "REGION_RATING_CLIENT": { "display_name": "居住地区评级", "description": "Our rating of the region where client lives (1,2,3)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "REGION_RATING_CLIENT_W_CITY": { "display_name": "考虑城市的居住地区评级", "description": "Our rating of the region where client lives with taking city into account (1,2,3)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "WEEKDAY_APPR_PROCESS_START": { "display_name": "申请星期", "description": "On which day of the week did the client apply for the loan", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "HOUR_APPR_PROCESS_START": { "display_name": "申请大致小时", "description": "Approximately at what hour did the client apply for the loan", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "REG_REGION_NOT_LIVE_REGION": { "display_name": "永久与联系地址地区是否不同", "description": "Flag if client's permanent address does not match contact address (1=different, 0=same, at region level)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "REG_REGION_NOT_WORK_REGION": { "display_name": "永久与工作地址地区是否不同", "description": "Flag if client's permanent address does not match work address (1=different, 0=same, at region level)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "LIVE_REGION_NOT_WORK_REGION": { "display_name": "联系与工作地址地区是否不同", "description": "Flag if client's contact address does not match work address (1=different, 0=same, at region level)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "REG_CITY_NOT_LIVE_CITY": { "display_name": "永久与联系地址城市是否不同", "description": "Flag if client's permanent address does not match contact address (1=different, 0=same, at city level)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "REG_CITY_NOT_WORK_CITY": { "display_name": "永久与工作地址城市是否不同", "description": "Flag if client's permanent address does not match work address (1=different, 0=same, at city level)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "LIVE_CITY_NOT_WORK_CITY": { "display_name": "联系与工作地址城市是否不同", "description": "Flag if client's contact address does not match work address (1=different, 0=same, at city level)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "ORGANIZATION_TYPE": { "display_name": "工作单位类型", "description": "Type of organization where client works", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "EXT_SOURCE_1": { "display_name": "外部来源分 1", "description": "Normalized score from external data source", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "EXT_SOURCE_2": { "display_name": "外部来源分 2", "description": "Normalized score from external data source", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "EXT_SOURCE_3": { "display_name": "外部来源分 3", "description": "Normalized score from external data source", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "APARTMENTS_AVG": { "display_name": "建筑公寓信息归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "BASEMENTAREA_AVG": { "display_name": "地下室面积归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "YEARS_BEGINEXPLUATATION_AVG": { "display_name": "建筑开始使用年限归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "YEARS_BUILD_AVG": { "display_name": "建筑建成年限归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "COMMONAREA_AVG": { "display_name": "公共区域面积归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "ELEVATORS_AVG": { "display_name": "电梯数量归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "ENTRANCES_AVG": { "display_name": "入口数量归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "FLOORSMAX_AVG": { "display_name": "最高楼层归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "FLOORSMIN_AVG": { "display_name": "最低楼层归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "LANDAREA_AVG": { "display_name": "土地面积归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "LIVINGAPARTMENTS_AVG": { "display_name": "居住公寓信息归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "LIVINGAREA_AVG": { "display_name": "居住面积归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "NONLIVINGAPARTMENTS_AVG": { "display_name": "非居住公寓信息归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "NONLIVINGAREA_AVG": { "display_name": "非居住面积归一化均值", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "APARTMENTS_MODE": { "display_name": "建筑公寓信息归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "BASEMENTAREA_MODE": { "display_name": "地下室面积归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "YEARS_BEGINEXPLUATATION_MODE": { "display_name": "建筑开始使用年限归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "YEARS_BUILD_MODE": { "display_name": "建筑建成年限归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "COMMONAREA_MODE": { "display_name": "公共区域面积归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "ELEVATORS_MODE": { "display_name": "电梯数量归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "ENTRANCES_MODE": { "display_name": "入口数量归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "FLOORSMAX_MODE": { "display_name": "最高楼层归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "FLOORSMIN_MODE": { "display_name": "最低楼层归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "LANDAREA_MODE": { "display_name": "土地面积归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "LIVINGAPARTMENTS_MODE": { "display_name": "居住公寓信息归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "LIVINGAREA_MODE": { "display_name": "居住面积归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "NONLIVINGAPARTMENTS_MODE": { "display_name": "非居住公寓信息归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "NONLIVINGAREA_MODE": { "display_name": "非居住面积归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "APARTMENTS_MEDI": { "display_name": "建筑公寓信息归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "BASEMENTAREA_MEDI": { "display_name": "地下室面积归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "YEARS_BEGINEXPLUATATION_MEDI": { "display_name": "建筑开始使用年限归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "YEARS_BUILD_MEDI": { "display_name": "建筑建成年限归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "COMMONAREA_MEDI": { "display_name": "公共区域面积归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "ELEVATORS_MEDI": { "display_name": "电梯数量归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "ENTRANCES_MEDI": { "display_name": "入口数量归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "FLOORSMAX_MEDI": { "display_name": "最高楼层归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "FLOORSMIN_MEDI": { "display_name": "最低楼层归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "LANDAREA_MEDI": { "display_name": "土地面积归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "LIVINGAPARTMENTS_MEDI": { "display_name": "居住公寓信息归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "LIVINGAREA_MEDI": { "display_name": "居住面积归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "NONLIVINGAPARTMENTS_MEDI": { "display_name": "非居住公寓信息归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "NONLIVINGAREA_MEDI": { "display_name": "非居住面积归一化中位数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "FONDKAPREMONT_MODE": { "display_name": "建筑信息 FONDKAPREMONT 众数（细项未公开）", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "HOUSETYPE_MODE": { "display_name": "住房类型众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "TOTALAREA_MODE": { "display_name": "建筑总面积归一化众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "WALLSMATERIAL_MODE": { "display_name": "墙体材料众数", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "EMERGENCYSTATE_MODE": { "display_name": "建筑状态信息众数（细项未公开）", "description": "Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "归一化值（无量纲）" }, "OBS_30_CNT_SOCIAL_CIRCLE": { "display_name": "社交圈可观察的 30 天逾期记录数", "description": "How many observation of client's social surroundings with observable 30 DPD (days past due) default", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "次数或人数（按官方定义）" }, "DEF_30_CNT_SOCIAL_CIRCLE": { "display_name": "社交圈发生 30 天逾期的记录数", "description": "How many observation of client's social surroundings defaulted on 30 DPD (days past due)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "次数或人数（按官方定义）" }, "OBS_60_CNT_SOCIAL_CIRCLE": { "display_name": "社交圈可观察的 60 天逾期记录数", "description": "How many observation of client's social surroundings with observable 60 DPD (days past due) default", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "次数或人数（按官方定义）" }, "DEF_60_CNT_SOCIAL_CIRCLE": { "display_name": "社交圈发生 60 天逾期的记录数", "description": "How many observation of client's social surroundings defaulted on 60 (days past due) DPD", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "次数或人数（按官方定义）" }, "DAYS_LAST_PHONE_CHANGE": { "display_name": "更换电话相对申请的天数", "description": "How many days before application did client change phone", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "天（相对申请日，保留原始符号）" }, "FLAG_DOCUMENT_2": { "display_name": "是否提供文件 2", "description": "Did client provide document 2", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_3": { "display_name": "是否提供文件 3", "description": "Did client provide document 3", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_4": { "display_name": "是否提供文件 4", "description": "Did client provide document 4", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_5": { "display_name": "是否提供文件 5", "description": "Did client provide document 5", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_6": { "display_name": "是否提供文件 6", "description": "Did client provide document 6", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_7": { "display_name": "是否提供文件 7", "description": "Did client provide document 7", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_8": { "display_name": "是否提供文件 8", "description": "Did client provide document 8", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_9": { "display_name": "是否提供文件 9", "description": "Did client provide document 9", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_10": { "display_name": "是否提供文件 10", "description": "Did client provide document 10", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_11": { "display_name": "是否提供文件 11", "description": "Did client provide document 11", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_12": { "display_name": "是否提供文件 12", "description": "Did client provide document 12", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_13": { "display_name": "是否提供文件 13", "description": "Did client provide document 13", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_14": { "display_name": "是否提供文件 14", "description": "Did client provide document 14", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_15": { "display_name": "是否提供文件 15", "description": "Did client provide document 15", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_16": { "display_name": "是否提供文件 16", "description": "Did client provide document 16", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_17": { "display_name": "是否提供文件 17", "description": "Did client provide document 17", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_18": { "display_name": "是否提供文件 18", "description": "Did client provide document 18", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_19": { "display_name": "是否提供文件 19", "description": "Did client provide document 19", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_20": { "display_name": "是否提供文件 20", "description": "Did client provide document 20", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "FLAG_DOCUMENT_21": { "display_name": "是否提供文件 21", "description": "Did client provide document 21", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "未公开" }, "AMT_REQ_CREDIT_BUREAU_HOUR": { "display_name": "申请前一小时征信查询次数", "description": "Number of enquiries to Credit Bureau about the client one hour before application", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "次数或人数（按官方定义）" }, "AMT_REQ_CREDIT_BUREAU_DAY": { "display_name": "申请前一天征信查询次数（不含前一小时）", "description": "Number of enquiries to Credit Bureau about the client one day before application (excluding one hour before application)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "次数或人数（按官方定义）" }, "AMT_REQ_CREDIT_BUREAU_WEEK": { "display_name": "申请前一周征信查询次数（不含前一天）", "description": "Number of enquiries to Credit Bureau about the client one week before application (excluding one day before application)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "次数或人数（按官方定义）" }, "AMT_REQ_CREDIT_BUREAU_MON": { "display_name": "申请前一个月征信查询次数（不含前一周）", "description": "Number of enquiries to Credit Bureau about the client one month before application (excluding one week before application)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "次数或人数（按官方定义）" }, "AMT_REQ_CREDIT_BUREAU_QRT": { "display_name": "申请前三个月征信查询次数（不含前一个月）", "description": "Number of enquiries to Credit Bureau about the client 3 month before application (excluding one month before application)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "次数或人数（按官方定义）" }, "AMT_REQ_CREDIT_BUREAU_YEAR": { "display_name": "申请前一年征信查询次数（官方说明原文有歧义）", "description": "Number of enquiries to Credit Bureau about the client one day year (excluding last 3 months before application)", "data_source": "Home Credit 2018 application_{train|test}.csv", "unit": "次数或人数（按官方定义）" } }, "source": { "kind": "analysis", "producer": "mars", "input_provenance": "caller_provided_dataframe" }, "context_source": { "business_context": { "label_definition": "unknown", "observation_window": "unknown", "currency": "unknown", "dataset_id": "user_provided", "source": "user_provided", "real_features": "user_provided", "target": "user_provided", "date": "user_provided", "partitions": "user_provided", "amount": "user_provided", "weights": "user_provided", "sample_scope": "user_provided", "preparation_version": "user_provided", "special_values": "user_provided", "labels": "user_provided" }, "parameters": "calculation" }, "serialization": { "non_finite": "tagged float: {$mars: float, value: nan/inf/-inf}", "date": "ISO-8601", "null": "missing; calculation state is separate" }, "tables": { "summary": { "rows": 119, "index": null, "grain": "feature", "fields": { "feature": { "dtype": "String", "unit": "identifier", "meaning": "原输入特征名称" }, "display_name": { "dtype": "String", "unit": "category", "meaning": "调用方校验后的特征可读名称；缺失可在展示时回退原始 ID" }, "dtype": { "dtype": "String", "unit": "type", "meaning": "原输入字段的数据类型" }, "data_source": { "dtype": "String", "unit": "category", "meaning": "调用方登记的特征来源；未映射字段可能标为 UNMAPPED" }, "iv": { "dtype": "Float32", "unit": "dimensionless", "meaning": "各箱 (bad_dist-good_dist)×WOE 之和，复用稳定化规则" }, "ks": { "dtype": "Float64", "unit": "points_0_100", "meaning": "按实际配置排序的分箱累计坏样本与好样本分布最大绝对差 ×100" }, "auc": { "dtype": "Float64", "unit": "ratio", "meaning": "按配置排序的分箱 ROC 梯形面积；报告归一到不小于 0.5" }, "psi_max": { "dtype": "Float64", "unit": "dimensionless", "meaning": "各箱 (actual-expected)×ln(actual/expected) 之和；参考及箱范围见参数；跨有效分组最大值" }, "rc_min": { "dtype": "Float64", "unit": "correlation", "meaning": "正常箱坏率与 RC 参考坏率的 Spearman 相关系数，参考来源见参数；跨有效分组最小值" }, "lift_min": { "dtype": "Float64", "unit": "dimensionless", "meaning": "Total 正常箱 Lift 的最小值" }, "lift_max": { "dtype": "Float64", "unit": "dimensionless", "meaning": "Total 正常箱 Lift 的最大值" }, "missing": { "dtype": "Float64", "unit": "ratio", "meaning": "缺失箱样本量/全样本量；画像包括 Null、NaN 和配置缺失值" }, "missing_min": { "dtype": "Float64", "unit": "ratio", "meaning": "缺失箱样本量/全样本量；画像包括 Null、NaN 和配置缺失值；跨有效分组最小值" }, "missing_max": { "dtype": "Float64", "unit": "ratio", "meaning": "缺失箱样本量/全样本量；画像包括 Null、NaN 和配置缺失值；跨有效分组最大值" }, "mono": { "dtype": "Float64", "unit": "correlation", "meaning": "Total 正常箱索引与坏率的 Spearman 相关系数；单箱或坏率恒定时无法定义" } } }, "detail": { "rows": 3257, "index": null, "grain": "target/feature/group/bin", "fields": { "y": { "dtype": "String", "unit": "identifier", "meaning": "目标列标识；真实目标及无标签状态见参数" }, "feature": { "dtype": "String", "unit": "identifier", "meaning": "原输入特征名称" }, "display_name": { "dtype": "String", "unit": "category", "meaning": "调用方校验后的特征可读名称；缺失可在展示时回退原始 ID" }, "dtype": { "dtype": "String", "unit": "type", "meaning": "原输入字段的数据类型" }, "data_source": { "dtype": "String", "unit": "category", "meaning": "调用方登记的特征来源；未映射字段可能标为 UNMAPPED" }, "trend": { "dtype": "String", "unit": "category", "meaning": "Total 正常箱 WOE 形态；无标签时未计算" }, "mars_group": { "dtype": "String", "unit": "dimension", "meaning": "实际计算分组字段；取值保留原始分组标识" }, "bin_index": { "dtype": "Int16", "unit": "index", "meaning": "分箱规则索引；缺失和特殊箱为负，汇总行由 bin_type 标识" }, "bin_label": { "dtype": "String", "unit": "category", "meaning": "来自拟合分箱规则的箱标签" }, "count": { "dtype": "Float64", "unit": "count", "meaning": "全样本数；配置 weights_col 时为样本权重和" }, "observed_count": { "dtype": "Float64", "unit": "count", "meaning": "已表现标签样本数或权重和；无标签时未计算" }, "bad": { "dtype": "Float64", "unit": "count", "meaning": "已表现坏样本数或权重和" }, "good": { "dtype": "Float64", "unit": "count", "meaning": "observed_count-bad" }, "pct": { "dtype": "Float64", "unit": "ratio", "meaning": "箱样本量/分组全样本量，配置权重时为权重和之比" }, "bad_rate": { "dtype": "Float64", "unit": "ratio", "meaning": "坏人数/有表现人数；加权时为坏权重/有表现权重，见 parameters" }, "lift": { "dtype": "Float64", "unit": "dimensionless", "meaning": "箱坏率/总体坏率，复用稳定化规则" }, "cum_count": { "dtype": "Float64", "unit": "count", "meaning": "按分箱索引展示顺序的累计全样本量或权重和" }, "cum_observed_count": { "dtype": "Float64", "unit": "count", "meaning": "按分箱索引展示顺序的累计已表现样本量或权重和" }, "cum_bad": { "dtype": "Float64", "unit": "count", "meaning": "按分箱索引展示顺序的累计坏样本量或权重和" }, "cum_bad_rate": { "dtype": "Float64", "unit": "ratio", "meaning": "累计 bad/累计 observed_count" }, "psi_bin": { "dtype": "Float64", "unit": "dimensionless", "meaning": "当前箱 PSI 贡献；缺失箱和特殊箱由参数控制" }, "ks_bin": { "dtype": "Float64", "unit": "points_0_100", "meaning": "当前箱累计坏样本与好样本分布绝对差 ×100" }, "auc_bin": { "dtype": "Float64", "unit": "ratio", "meaning": "分箱 ROC 梯形面积贡献；汇总行进行 AUC 归一" }, "iv_bin": { "dtype": "Float32", "unit": "dimensionless", "meaning": "(bad_dist-good_dist)×WOE" }, "total_count": { "dtype": "Float64", "unit": "count", "meaning": "分组全样本数或权重和" }, "bin_type": { "dtype": "String", "unit": "category", "meaning": "正常、缺失、特殊或汇总箱类型" }, "tot_amt": { "dtype": "Float64", "unit": "unknown_business_unit", "meaning": "全样本金金额和；业务币种未知" }, "good_amt": { "dtype": "Float64", "unit": "unknown_business_unit", "meaning": "好样本金金额和；业务币种未知" }, "bad_amt": { "dtype": "Float64", "unit": "unknown_business_unit", "meaning": "坏样本金金额和；业务币种未知" }, "avg_amt": { "dtype": "Float64", "unit": "unknown_business_unit", "meaning": "tot_amt/count；配置样本权重时 count 为权重和；业务币种未知" }, "amt_bad_rate": { "dtype": "Float64", "unit": "ratio", "meaning": "bad_amt/observed_amt；未表现金额不计入分母，分母非正时为空" }, "lift_amt": { "dtype": "Float64", "unit": "dimensionless", "meaning": "箱金额坏率/总体金额坏率，复用稳定化规则" } } }, "trend.psi": { "rows": 119, "index": null, "grain": "feature (groups in columns)", "fields": { "feature": { "dtype": "String", "unit": "identifier", "meaning": "原输入特征名称" }, "display_name": { "dtype": "String", "unit": "category", "meaning": "调用方校验后的特征可读名称；缺失可在展示时回退原始 ID" }, "dtype": { "dtype": "String", "unit": "type", "meaning": "原输入字段的数据类型" }, "data_source": { "dtype": "String", "unit": "category", "meaning": "调用方登记的特征来源；未映射字段可能标为 UNMAPPED" }, "0train": { "dtype": "Float64", "unit": "dimensionless", "meaning": "各箱 (actual-expected)×ln(actual/expected) 之和；参考及箱范围见参数" }, "1val": { "dtype": "Float64", "unit": "dimensionless", "meaning": "各箱 (actual-expected)×ln(actual/expected) 之和；参考及箱范围见参数" }, "2test": { "dtype": "Float64", "unit": "dimensionless", "meaning": "各箱 (actual-expected)×ln(actual/expected) 之和；参考及箱范围见参数" }, "3oot": { "dtype": "Float64", "unit": "dimensionless", "meaning": "各箱 (actual-expected)×ln(actual/expected) 之和；参考及箱范围见参数" }, "4_oot_undue": { "dtype": "Float64", "unit": "dimensionless", "meaning": "各箱 (actual-expected)×ln(actual/expected) 之和；参考及箱范围见参数" }, "Total": { "dtype": "Float64", "unit": "dimensionless", "meaning": "各箱 (actual-expected)×ln(actual/expected) 之和；参考及箱范围见参数" } }, "target": "TARGET" }, "trend.auc": { "rows": 119, "index": null, "grain": "feature (groups in columns)", "fields": { "feature": { "dtype": "String", "unit": "identifier", "meaning": "原输入特征名称" }, "display_name": { "dtype": "String", "unit": "category", "meaning": "调用方校验后的特征可读名称；缺失可在展示时回退原始 ID" }, "dtype": { "dtype": "String", "unit": "type", "meaning": "原输入字段的数据类型" }, "data_source": { "dtype": "String", "unit": "category", "meaning": "调用方登记的特征来源；未映射字段可能标为 UNMAPPED" }, "0train": { "dtype": "Float64", "unit": "ratio", "meaning": "按配置排序的分箱 ROC 梯形面积；报告归一到不小于 0.5" }, "1val": { "dtype": "Float64", "unit": "ratio", "meaning": "按配置排序的分箱 ROC 梯形面积；报告归一到不小于 0.5" }, "2test": { "dtype": "Float64", "unit": "ratio", "meaning": "按配置排序的分箱 ROC 梯形面积；报告归一到不小于 0.5" }, "3oot": { "dtype": "Float64", "unit": "ratio", "meaning": "按配置排序的分箱 ROC 梯形面积；报告归一到不小于 0.5" }, "4_oot_undue": { "dtype": "Float64", "unit": "ratio", "meaning": "按配置排序的分箱 ROC 梯形面积；报告归一到不小于 0.5" }, "Total": { "dtype": "Float64", "unit": "ratio", "meaning": "按配置排序的分箱 ROC 梯形面积；报告归一到不小于 0.5" } }, "target": "TARGET" }, "trend.ks": { "rows": 119, "index": null, "grain": "feature (groups in columns)", "fields": { "feature": { "dtype": "String", "unit": "identifier", "meaning": "原输入特征名称" }, "display_name": { "dtype": "String", "unit": "category", "meaning": "调用方校验后的特征可读名称；缺失可在展示时回退原始 ID" }, "dtype": { "dtype": "String", "unit": "type", "meaning": "原输入字段的数据类型" }, "data_source": { "dtype": "String", "unit": "category", "meaning": "调用方登记的特征来源；未映射字段可能标为 UNMAPPED" }, "0train": { "dtype": "Float64", "unit": "points_0_100", "meaning": "按实际配置排序的分箱累计坏样本与好样本分布最大绝对差 ×100" }, "1val": { "dtype": "Float64", "unit": "points_0_100", "meaning": "按实际配置排序的分箱累计坏样本与好样本分布最大绝对差 ×100" }, "2test": { "dtype": "Float64", "unit": "points_0_100", "meaning": "按实际配置排序的分箱累计坏样本与好样本分布最大绝对差 ×100" }, "3oot": { "dtype": "Float64", "unit": "points_0_100", "meaning": "按实际配置排序的分箱累计坏样本与好样本分布最大绝对差 ×100" }, "4_oot_undue": { "dtype": "Float64", "unit": "points_0_100", "meaning": "按实际配置排序的分箱累计坏样本与好样本分布最大绝对差 ×100" }, "Total": { "dtype": "Float64", "unit": "points_0_100", "meaning": "按实际配置排序的分箱累计坏样本与好样本分布最大绝对差 ×100" } }, "target": "TARGET" }, "trend.iv": { "rows": 119, "index": null, "grain": "feature (groups in columns)", "fields": { "feature": { "dtype": "String", "unit": "identifier", "meaning": "原输入特征名称" }, "display_name": { "dtype": "String", "unit": "category", "meaning": "调用方校验后的特征可读名称；缺失可在展示时回退原始 ID" }, "dtype": { "dtype": "String", "unit": "type", "meaning": "原输入字段的数据类型" }, "data_source": { "dtype": "String", "unit": "category", "meaning": "调用方登记的特征来源；未映射字段可能标为 UNMAPPED" }, "0train": { "dtype": "Float32", "unit": "dimensionless", "meaning": "各箱 (bad_dist-good_dist)×WOE 之和，复用稳定化规则" }, "1val": { "dtype": "Float32", "unit": "dimensionless", "meaning": "各箱 (bad_dist-good_dist)×WOE 之和，复用稳定化规则" }, "2test": { "dtype": "Float32", "unit": "dimensionless", "meaning": "各箱 (bad_dist-good_dist)×WOE 之和，复用稳定化规则" }, "3oot": { "dtype": "Float32", "unit": "dimensionless", "meaning": "各箱 (bad_dist-good_dist)×WOE 之和，复用稳定化规则" }, "4_oot_undue": { "dtype": "Float32", "unit": "dimensionless", "meaning": "各箱 (bad_dist-good_dist)×WOE 之和，复用稳定化规则" }, "Total": { "dtype": "Float32", "unit": "dimensionless", "meaning": "各箱 (bad_dist-good_dist)×WOE 之和，复用稳定化规则" } }, "target": "TARGET" }, "trend.missing": { "rows": 119, "index": null, "grain": "feature (groups in columns)", "fields": { "feature": { "dtype": "String", "unit": "identifier", "meaning": "原输入特征名称" }, "display_name": { "dtype": "String", "unit": "category", "meaning": "调用方校验后的特征可读名称；缺失可在展示时回退原始 ID" }, "dtype": { "dtype": "String", "unit": "type", "meaning": "原输入字段的数据类型" }, "data_source": { "dtype": "String", "unit": "category", "meaning": "调用方登记的特征来源；未映射字段可能标为 UNMAPPED" }, "0train": { "dtype": "Float64", "unit": "ratio", "meaning": "缺失箱样本量/全样本量；画像包括 Null、NaN 和配置缺失值" }, "1val": { "dtype": "Float64", "unit": "ratio", "meaning": "缺失箱样本量/全样本量；画像包括 Null、NaN 和配置缺失值" }, "2test": { "dtype": "Float64", "unit": "ratio", "meaning": "缺失箱样本量/全样本量；画像包括 Null、NaN 和配置缺失值" }, "3oot": { "dtype": "Float64", "unit": "ratio", "meaning": "缺失箱样本量/全样本量；画像包括 Null、NaN 和配置缺失值" }, "4_oot_undue": { "dtype": "Float64", "unit": "ratio", "meaning": "缺失箱样本量/全样本量；画像包括 Null、NaN 和配置缺失值" }, "Total": { "dtype": "Float64", "unit": "ratio", "meaning": "缺失箱样本量/全样本量；画像包括 Null、NaN 和配置缺失值" } }, "target": "TARGET" }, "trend.lift": { "rows": 119, "index": null, "grain": "feature (groups in columns)", "fields": { "feature": { "dtype": "String", "unit": "identifier", "meaning": "原输入特征名称" }, "display_name": { "dtype": "String", "unit": "category", "meaning": "调用方校验后的特征可读名称；缺失可在展示时回退原始 ID" }, "dtype": { "dtype": "String", "unit": "type", "meaning": "原输入字段的数据类型" }, "data_source": { "dtype": "String", "unit": "category", "meaning": "调用方登记的特征来源；未映射字段可能标为 UNMAPPED" }, "0train": { "dtype": "Float64", "unit": "dimensionless", "meaning": "当前分组箱 Lift 的最大值；未表现分组为空" }, "1val": { "dtype": "Float64", "unit": "dimensionless", "meaning": "当前分组箱 Lift 的最大值；未表现分组为空" }, "2test": { "dtype": "Float64", "unit": "dimensionless", "meaning": "当前分组箱 Lift 的最大值；未表现分组为空" }, "3oot": { "dtype": "Float64", "unit": "dimensionless", "meaning": "当前分组箱 Lift 的最大值；未表现分组为空" }, "4_oot_undue": { "dtype": "Float64", "unit": "dimensionless", "meaning": "当前分组箱 Lift 的最大值；未表现分组为空" }, "Total": { "dtype": "Float64", "unit": "dimensionless", "meaning": "当前分组箱 Lift 的最大值；未表现分组为空" } }, "target": "TARGET" }, "trend.risk_corr": { "rows": 119, "index": null, "grain": "feature (groups in columns)", "fields": { "feature": { "dtype": "String", "unit": "identifier", "meaning": "原输入特征名称" }, "display_name": { "dtype": "String", "unit": "category", "meaning": "调用方校验后的特征可读名称；缺失可在展示时回退原始 ID" }, "dtype": { "dtype": "String", "unit": "type", "meaning": "原输入字段的数据类型" }, "data_source": { "dtype": "String", "unit": "category", "meaning": "调用方登记的特征来源；未映射字段可能标为 UNMAPPED" }, "0train": { "dtype": "Float64", "unit": "correlation", "meaning": "正常箱坏率与 RC 参考坏率的 Spearman 相关系数，参考来源见参数" }, "1val": { "dtype": "Float64", "unit": "correlation", "meaning": "正常箱坏率与 RC 参考坏率的 Spearman 相关系数，参考来源见参数" }, "2test": { "dtype": "Float64", "unit": "correlation", "meaning": "正常箱坏率与 RC 参考坏率的 Spearman 相关系数，参考来源见参数" }, "3oot": { "dtype": "Float64", "unit": "correlation", "meaning": "正常箱坏率与 RC 参考坏率的 Spearman 相关系数，参考来源见参数" }, "4_oot_undue": { "dtype": "Float64", "unit": "correlation", "meaning": "正常箱坏率与 RC 参考坏率的 Spearman 相关系数，参考来源见参数" }, "Total": { "dtype": "Float64", "unit": "correlation", "meaning": "正常箱坏率与 RC 参考坏率的 Spearman 相关系数，参考来源见参数" } }, "target": "TARGET" }, "calculation_status": { "rows": 833, "index": null, "grain": "target/feature/group/metric", "fields": { "feature": { "dtype": "String", "unit": "identifier", "meaning": "原输入特征名称" }, "display_name": { "dtype": "String", "unit": "category", "meaning": "调用方校验后的特征可读名称；缺失可在展示时回退原始 ID" }, "dtype": { "dtype": "String", "unit": "type", "meaning": "原输入字段的数据类型" }, "data_source": { "dtype": "String", "unit": "category", "meaning": "调用方登记的特征来源；未映射字段可能标为 UNMAPPED" }, "target": { "dtype": "String", "unit": "identifier", "meaning": "真实目标列标识" }, "group": { "dtype": "String", "unit": "dimension", "meaning": "状态所属分组；Total 为全量" }, "metric": { "dtype": "String", "unit": "identifier", "meaning": "计算状态适用的指标或指标族" }, "status": { "dtype": "String", "unit": "state", "meaning": "computed 已计算（有效零仍为零）；not_computed 未计算；unobserved 无观测标签；undefined 无法定义；insufficient_samples 样本不足；failed 计算失败；skipped 跳过；结合 reason" }, "reason": { "dtype": "String", "unit": "state_reason", "meaning": "no_target 未提供目标；no_observed_labels 无已观测标签；single_observed_class 仅一种观测类别；其他失败、跳过、样本不足或无法定义原因；空值不替代有效零" } } }, "missing_by_day": { "rows": 119, "index": null, "grain": "feature (days in columns)", "fields": { "feature": { "dtype": "String", "unit": "identifier", "meaning": "原输入特征名称" }, "display_name": { "dtype": "String", "unit": "category", "meaning": "调用方校验后的特征可读名称；缺失可在展示时回退原始 ID" }, "dtype": { "dtype": "String", "unit": "type", "meaning": "原输入字段的数据类型" }, "data_source": { "dtype": "String", "unit": "category", "meaning": "调用方登记的特征来源；未映射字段可能标为 UNMAPPED" }, "2026-01-01": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-02": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-03": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-04": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-05": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-06": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-07": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-08": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-09": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-10": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-11": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-12": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-13": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-14": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-15": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-16": { "dtype": "Float64", "unit": "ratio", "meaning": "自然日原始缺失值数/当日样本数，含 Null、NaN 和配置缺失值；不使用样本权重，total 为全量比例" }, "2026-01-17": { "dtype": 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0.019626802501047477, "Total": 0.0003571674042553145 }, { "feature": "DAYS_BIRTH", "display_name": "申请时年龄天数（原始值）", "dtype": "Int64", "data_source": "Home Credit 2018 application_{train|test}.csv", "0train": 0.0, "1val": 0.00019318049994567635, "2test": 5.738890739344055e-05, "3oot": 1.3160977549045254e-05, "4_oot_undue": 0.0003745251611204983, "Total": 1.121537915945457e-05 }, { "feature": "EXT_SOURCE_2", "display_name": "外部来源分 2", "dtype": "Float64", "data_source": "Home Credit 2018 application_{train|test}.csv", "0train": 0.0, "1val": 0.00011481227134160583, "2test": 0.00035869382425640894, "3oot": 0.00011556668820521128, "4_oot_undue": 0.006740861911165587, "Total": 0.0001399751806666898 }, { "feature": "EXT_SOURCE_3", "display_name": "外部来源分 3", "dtype": "Float64", "data_source": "Home Credit 2018 application_{train|test}.csv", "0train": 0.0, "1val": 3.0691627578954246e-05, "2test": 4.113556207281732e-05, "3oot": 0.00018583162422911403, "4_oot_undue": 0.00506146451724824, "Total": 6.475438326131638e-05 } ] }, "reference_row_count": 215374, "targets": [ "TARGET" ], "candidate_features": [ "NAME_CONTRACT_TYPE", "CODE_GENDER", "FLAG_OWN_CAR", "FLAG_OWN_REALTY", "CNT_CHILDREN", "AMT_INCOME_TOTAL", "AMT_ANNUITY", "AMT_GOODS_PRICE", "NAME_TYPE_SUITE", "NAME_INCOME_TYPE", "NAME_EDUCATION_TYPE", "NAME_FAMILY_STATUS", "NAME_HOUSING_TYPE", "REGION_POPULATION_RELATIVE", "DAYS_BIRTH", "DAYS_EMPLOYED", "DAYS_REGISTRATION", "DAYS_ID_PUBLISH", "OWN_CAR_AGE", "FLAG_MOBIL", "FLAG_EMP_PHONE", "FLAG_WORK_PHONE", "FLAG_CONT_MOBILE", "FLAG_PHONE", "FLAG_EMAIL", "OCCUPATION_TYPE", "CNT_FAM_MEMBERS", "REGION_RATING_CLIENT", "REGION_RATING_CLIENT_W_CITY", "WEEKDAY_APPR_PROCESS_START", "HOUR_APPR_PROCESS_START", "REG_REGION_NOT_LIVE_REGION", "REG_REGION_NOT_WORK_REGION", "LIVE_REGION_NOT_WORK_REGION", "REG_CITY_NOT_LIVE_CITY", "REG_CITY_NOT_WORK_CITY", "LIVE_CITY_NOT_WORK_CITY", "ORGANIZATION_TYPE", "EXT_SOURCE_1", "EXT_SOURCE_2", "EXT_SOURCE_3", "APARTMENTS_AVG", "BASEMENTAREA_AVG", "YEARS_BEGINEXPLUATATION_AVG", "YEARS_BUILD_AVG", "COMMONAREA_AVG", "ELEVATORS_AVG", "ENTRANCES_AVG", "FLOORSMAX_AVG", "FLOORSMIN_AVG", "LANDAREA_AVG", "LIVINGAPARTMENTS_AVG", "LIVINGAREA_AVG", "NONLIVINGAPARTMENTS_AVG", "NONLIVINGAREA_AVG", "APARTMENTS_MODE", "BASEMENTAREA_MODE", "YEARS_BEGINEXPLUATATION_MODE", "YEARS_BUILD_MODE", "COMMONAREA_MODE", "ELEVATORS_MODE", "ENTRANCES_MODE", "FLOORSMAX_MODE", "FLOORSMIN_MODE", "LANDAREA_MODE", "LIVINGAPARTMENTS_MODE", "LIVINGAREA_MODE", "NONLIVINGAPARTMENTS_MODE", "NONLIVINGAREA_MODE", "APARTMENTS_MEDI", "BASEMENTAREA_MEDI", "YEARS_BEGINEXPLUATATION_MEDI", "YEARS_BUILD_MEDI", "COMMONAREA_MEDI", "ELEVATORS_MEDI", "ENTRANCES_MEDI", "FLOORSMAX_MEDI", "FLOORSMIN_MEDI", "LANDAREA_MEDI", "LIVINGAPARTMENTS_MEDI", "LIVINGAREA_MEDI", "NONLIVINGAPARTMENTS_MEDI", "NONLIVINGAREA_MEDI", "FONDKAPREMONT_MODE", "HOUSETYPE_MODE", "TOTALAREA_MODE", "WALLSMATERIAL_MODE", "EMERGENCYSTATE_MODE", "OBS_30_CNT_SOCIAL_CIRCLE", "DEF_30_CNT_SOCIAL_CIRCLE", "OBS_60_CNT_SOCIAL_CIRCLE", "DEF_60_CNT_SOCIAL_CIRCLE", "DAYS_LAST_PHONE_CHANGE", "FLAG_DOCUMENT_2", "FLAG_DOCUMENT_3", "FLAG_DOCUMENT_4", "FLAG_DOCUMENT_5", "FLAG_DOCUMENT_6", "FLAG_DOCUMENT_7", "FLAG_DOCUMENT_8", "FLAG_DOCUMENT_9", "FLAG_DOCUMENT_10", "FLAG_DOCUMENT_11", "FLAG_DOCUMENT_12", "FLAG_DOCUMENT_13", "FLAG_DOCUMENT_14", "FLAG_DOCUMENT_15", "FLAG_DOCUMENT_16", "FLAG_DOCUMENT_17", "FLAG_DOCUMENT_18", "FLAG_DOCUMENT_19", "FLAG_DOCUMENT_20", "FLAG_DOCUMENT_21", "AMT_REQ_CREDIT_BUREAU_HOUR", "AMT_REQ_CREDIT_BUREAU_DAY", "AMT_REQ_CREDIT_BUREAU_WEEK", "AMT_REQ_CREDIT_BUREAU_MON", "AMT_REQ_CREDIT_BUREAU_QRT", "AMT_REQ_CREDIT_BUREAU_YEAR" ], "analyzed_features": [ "NAME_CONTRACT_TYPE", "CODE_GENDER", "FLAG_OWN_CAR", "FLAG_OWN_REALTY", "CNT_CHILDREN", "AMT_INCOME_TOTAL", "AMT_ANNUITY", "AMT_GOODS_PRICE", "NAME_TYPE_SUITE", "NAME_INCOME_TYPE", "NAME_EDUCATION_TYPE", "NAME_FAMILY_STATUS", "NAME_HOUSING_TYPE", "REGION_POPULATION_RELATIVE", "DAYS_BIRTH", "DAYS_EMPLOYED", "DAYS_REGISTRATION", "DAYS_ID_PUBLISH", "OWN_CAR_AGE", "FLAG_MOBIL", "FLAG_EMP_PHONE", "FLAG_WORK_PHONE", "FLAG_CONT_MOBILE", "FLAG_PHONE", "FLAG_EMAIL", "OCCUPATION_TYPE", "CNT_FAM_MEMBERS", "REGION_RATING_CLIENT", "REGION_RATING_CLIENT_W_CITY", "WEEKDAY_APPR_PROCESS_START", "HOUR_APPR_PROCESS_START", "REG_REGION_NOT_LIVE_REGION", "REG_REGION_NOT_WORK_REGION", "LIVE_REGION_NOT_WORK_REGION", "REG_CITY_NOT_LIVE_CITY", "REG_CITY_NOT_WORK_CITY", "LIVE_CITY_NOT_WORK_CITY", "ORGANIZATION_TYPE", "EXT_SOURCE_1", "EXT_SOURCE_2", "EXT_SOURCE_3", "APARTMENTS_AVG", "BASEMENTAREA_AVG", "YEARS_BEGINEXPLUATATION_AVG", "YEARS_BUILD_AVG", "COMMONAREA_AVG", "ELEVATORS_AVG", "ENTRANCES_AVG", "FLOORSMAX_AVG", "FLOORSMIN_AVG", "LANDAREA_AVG", "LIVINGAPARTMENTS_AVG", "LIVINGAREA_AVG", "NONLIVINGAPARTMENTS_AVG", "NONLIVINGAREA_AVG", "APARTMENTS_MODE", "BASEMENTAREA_MODE", "YEARS_BEGINEXPLUATATION_MODE", "YEARS_BUILD_MODE", "COMMONAREA_MODE", "ELEVATORS_MODE", "ENTRANCES_MODE", "FLOORSMAX_MODE", "FLOORSMIN_MODE", "LANDAREA_MODE", "LIVINGAPARTMENTS_MODE", "LIVINGAREA_MODE", "NONLIVINGAPARTMENTS_MODE", "NONLIVINGAREA_MODE", "APARTMENTS_MEDI", "BASEMENTAREA_MEDI", "YEARS_BEGINEXPLUATATION_MEDI", "YEARS_BUILD_MEDI", "COMMONAREA_MEDI", "ELEVATORS_MEDI", "ENTRANCES_MEDI", "FLOORSMAX_MEDI", "FLOORSMIN_MEDI", "LANDAREA_MEDI", "LIVINGAPARTMENTS_MEDI", "LIVINGAREA_MEDI", "NONLIVINGAPARTMENTS_MEDI", "NONLIVINGAREA_MEDI", "FONDKAPREMONT_MODE", "HOUSETYPE_MODE", "TOTALAREA_MODE", "WALLSMATERIAL_MODE", "EMERGENCYSTATE_MODE", "OBS_30_CNT_SOCIAL_CIRCLE", "DEF_30_CNT_SOCIAL_CIRCLE", "OBS_60_CNT_SOCIAL_CIRCLE", "DEF_60_CNT_SOCIAL_CIRCLE", "DAYS_LAST_PHONE_CHANGE", "FLAG_DOCUMENT_2", "FLAG_DOCUMENT_3", "FLAG_DOCUMENT_4", "FLAG_DOCUMENT_5", "FLAG_DOCUMENT_6", "FLAG_DOCUMENT_7", "FLAG_DOCUMENT_8", "FLAG_DOCUMENT_9", "FLAG_DOCUMENT_10", "FLAG_DOCUMENT_11", "FLAG_DOCUMENT_12", "FLAG_DOCUMENT_13", "FLAG_DOCUMENT_14", "FLAG_DOCUMENT_15", "FLAG_DOCUMENT_16", "FLAG_DOCUMENT_17", "FLAG_DOCUMENT_18", "FLAG_DOCUMENT_19", "FLAG_DOCUMENT_20", "FLAG_DOCUMENT_21", "AMT_REQ_CREDIT_BUREAU_HOUR", "AMT_REQ_CREDIT_BUREAU_DAY", "AMT_REQ_CREDIT_BUREAU_WEEK", "AMT_REQ_CREDIT_BUREAU_MON", "AMT_REQ_CREDIT_BUREAU_QRT", "AMT_REQ_CREDIT_BUREAU_YEAR" ], "display_features": [ "EXT_SOURCE_2", "EXT_SOURCE_3", "EXT_SOURCE_1", "AMT_INCOME_TOTAL", "DAYS_BIRTH", "DAYS_EMPLOYED", "AMT_ANNUITY", "AMT_GOODS_PRICE", "NAME_INCOME_TYPE", "NAME_EDUCATION_TYPE", "NAME_CONTRACT_TYPE", "CODE_GENDER", "FLAG_OWN_CAR", "FLAG_OWN_REALTY", "CNT_CHILDREN", "OCCUPATION_TYPE", "REGION_POPULATION_RELATIVE", "DAYS_REGISTRATION", "DAYS_ID_PUBLISH", "CNT_FAM_MEMBERS" ], "primary_feature": "EXT_SOURCE_2", "time_report_id": "8b0d3d92-5d51-4afe-b8ae-69e7245f85c9", "units": { "ks": "0-100 percentage points", "bad_rate": "fraction", "iv": "dimensionless", "psi": "dimensionless" } }, "unavailable": "模拟日期不能证明真实跨期泛化；无标签组只有分布/PSI，没有可观测坏率或 KS。" }