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229 lines
14 KiB
229 lines
14 KiB
{
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"menu.engine.mv": "模型验证工具",
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"menu.engine.mv.config": "配置",
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"menu.engine.mv.config.cutOffPoint": "评分截断点",
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"menu.engine.mv.config.threshold": "预警阈值",
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"menu.engine.mv.config.binomial": "二项检验Z值常量",
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"menu.engine.mv.config.chiSquare": "卡方检验临界值常量",
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"menu.engine.mv.config.model": "模型",
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"menu.engine.mv.config.distribution": "建模时评分分布",
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"menu.engine.mv.config.scale": "标尺",
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"menu.engine.mv.config.dataExtractor": "数据抽取器接口",
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"menu.engine.mv.config.executor": "执行器",
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"menu.engine.mv.sample": "样本管理",
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"menu.engine.mv.result": "验证结果查看",
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"io.sc.engine.mv.enums.GoodLevel.POOR": "差",
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"io.sc.engine.mv.enums.GoodLevel.MEDIUM": "中等",
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"io.sc.engine.mv.enums.GoodLevel.GOOD": "好",
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"io.sc.engine.mv.enums.GoodLevel.VERY_GOOD": "很好",
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"io.sc.engine.mv.enums.GoodLevel.EXCELLENT": "非常好",
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"io.sc.engine.mv.enums.GoodLevel.PERFECT": "完美",
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"io.sc.engine.mv.enums.Stability.yes": "模型比较稳定",
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"io.sc.engine.mv.enums.Stability.no": "模型发生了偏移",
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"io.sc.engine.mv.config.cutOffPoint.grid.title": "评分截断点配置列表",
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"io.sc.engine.mv.config.cutOffPoint.grid.entity.name": "名称",
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"io.sc.engine.mv.config.cutOffPoint.grid.entity.from": "起始值(含)",
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"io.sc.engine.mv.config.cutOffPoint.grid.entity.to": "结束值(含)",
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"io.sc.engine.mv.config.cutOffPoint.grid.entity.step": "增量值",
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"io.sc.engine.mv.config.cutOffPoint.grid.entity.scale": "精度",
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"io.sc.engine.mv.config.threshold.grid.title": "预警阈值配置列表",
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"io.sc.engine.mv.config.threshold.grid.entity.name": "名称",
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"io.sc.engine.mv.config.threshold.grid.entity.level": "等级(越大越好)",
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"io.sc.engine.mv.config.threshold.grid.entity.color": "颜色",
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"io.sc.engine.mv.config.threshold.grid.entity.range": "预警阈值范围",
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"io.sc.engine.mv.config.threshold.grid.entity.quantitativeRange": "预警阈值范围(定量)",
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"io.sc.engine.mv.config.threshold.grid.entity.qualitativeRange": "预警阈值范围(定性)",
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"io.sc.engine.mv.config.binomial.grid.title": "二项检验标准正态分布显著水平下的Z值常量列表",
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"io.sc.engine.mv.config.binomial.grid.entity.significanceLevel": "显著水平",
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"io.sc.engine.mv.config.binomial.grid.entity.confidenceLevel": "置信水平",
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"io.sc.engine.mv.config.binomial.grid.entity.zUpper": "Z值上界",
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"io.sc.engine.mv.config.binomial.grid.entity.zLower": "Z值下界",
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"io.sc.engine.mv.config.chiSquare.grid.title": "卡方分布临界值常量",
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"io.sc.engine.mv.config.chiSquare.grid.entity.dof": "自由度",
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"io.sc.engine.mv.config.chiSquare.grid.entity.significanceLevel": "显著水平",
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"io.sc.engine.mv.config.chiSquare.grid.entity.criticalValue": "临界值",
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"io.sc.engine.mv.config.model.grid.title": "模型列表",
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"io.sc.engine.mv.config.model.grid.toolbar.importFromScoreRecordTable": "从评分记录表中导入",
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"io.sc.engine.mv.config.model.grid.entity.type": "模型创建类型",
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"io.sc.engine.mv.config.model.grid.entity.modelId": "模型标识",
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"io.sc.engine.mv.config.model.grid.entity.modelName": "模型名称",
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"io.sc.engine.mv.config.model.grid.action.importFromScoreRecord": "您确定要从评级记录表中导入模型?",
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"io.sc.engine.mv.config.distribution.grid.title": "咨询建模时样本分布情况配置列表",
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"io.sc.engine.mv.config.distribution.grid.entity.modelId": "模型标识",
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"io.sc.engine.mv.config.distribution.grid.entity.modelName": "模型名称",
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"io.sc.engine.mv.config.distribution.grid.entity.scoreSegStart": "分数段开始值(含该值)",
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"io.sc.engine.mv.config.distribution.grid.entity.scoreSegEnd": "分数段结束值(含该值)",
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"io.sc.engine.mv.config.distribution.grid.entity.count": "评分段内样本个数",
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"io.sc.engine.mv.config.scale.grid.title": "标尺列表",
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"io.sc.engine.mv.config.scale.grid.entity.modelId": "模型标识",
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"io.sc.engine.mv.config.scale.grid.entity.modelName": "模型名称",
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"io.sc.engine.mv.config.scale.grid.entity.level": "等级",
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"io.sc.engine.mv.config.scale.grid.entity.pd": "违约概率",
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"io.sc.engine.mv.config.scale.grid.entity.order": "排序",
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"io.sc.engine.mv.config.dataExtractor.grid.title": "数据抽取器列表",
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"io.sc.engine.mv.config.dataExtractor.grid.toolbar.example": "导入示例",
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"io.sc.engine.mv.config.dataExtractor.grid.toolbar.example.tip": "您确定要导入示例数据抽取器吗?",
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"io.sc.engine.mv.config.dataExtractor.grid.entity.datasourceName": "外部数据源名称",
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"io.sc.engine.mv.config.dataExtractor.grid.entity.executeTimeWeight": "预计执行时间权重",
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"io.sc.engine.mv.config.dataExtractor.grid.entity.groovyScript": "Groovy 脚本",
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"io.sc.engine.mv.config.executor.grid.title": "执行器列表",
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"io.sc.engine.mv.sample.action.importExampleSample": "导入示例样本",
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"io.sc.engine.mv.sample.action.importExampleSample.tip": "您确定要导入示例样本吗?",
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"io.sc.engine.mv.sample.action.removeAllSample": "删除所有样本",
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"io.sc.engine.mv.sample.action.removeAllSample.tip": "您确定要删除所有样本吗?",
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"io.sc.engine.mv.sample.tabs.sample": "合格样本",
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"io.sc.engine.mv.sample.tabs.scoreRecord": "评分记录",
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"io.sc.engine.mv.sample.tabs.defaultRecord": "违约记录",
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"io.sc.engine.mv.sample.sample.grid.title": "合格样本列表",
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"io.sc.engine.mv.sample.sample.grid.entity.validateDate": "验证日期",
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"io.sc.engine.mv.sample.sample.grid.entity.customId": "客户标识",
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"io.sc.engine.mv.sample.sample.grid.entity.customName": "客户名称",
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"io.sc.engine.mv.sample.sample.grid.entity.modelId": "模型标识",
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"io.sc.engine.mv.sample.sample.grid.entity.modelName": "模型名称",
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"io.sc.engine.mv.sample.sample.grid.entity.pd": "违约概率",
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"io.sc.engine.mv.sample.sample.grid.entity.score": "评分",
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"io.sc.engine.mv.sample.sample.grid.entity.scoreQuantitative": "定量评分",
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"io.sc.engine.mv.sample.sample.grid.entity.scoreQualitative": "定性评分",
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"io.sc.engine.mv.sample.sample.grid.entity.level": "等级",
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"io.sc.engine.mv.sample.sample.grid.entity.beginDate": "评分开始日期",
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"io.sc.engine.mv.sample.sample.grid.entity.endDate": "评分结束日期",
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"io.sc.engine.mv.sample.sample.grid.entity.defaultConfirmDate": "违约确定日期",
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"io.sc.engine.mv.sample.scoreRecord.grid.title": "评分记录列表",
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"io.sc.engine.mv.sample.scoreRecord.grid.entity.customId": "客户标识",
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"io.sc.engine.mv.sample.scoreRecord.grid.entity.customName": "客户名称",
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"io.sc.engine.mv.sample.scoreRecord.grid.entity.modelId": "模型标识",
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"io.sc.engine.mv.sample.scoreRecord.grid.entity.modelName": "模型名称",
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"io.sc.engine.mv.sample.scoreRecord.grid.entity.pd": "违约概率",
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"io.sc.engine.mv.sample.scoreRecord.grid.entity.score": "评分",
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"io.sc.engine.mv.sample.scoreRecord.grid.entity.scoreQuantitative": "定量评分",
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"io.sc.engine.mv.sample.scoreRecord.grid.entity.scoreQualitative": "定性评分",
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"io.sc.engine.mv.sample.scoreRecord.grid.entity.level": "等级",
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"io.sc.engine.mv.sample.scoreRecord.grid.entity.scoreBeginDate": "评分开始日期",
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"io.sc.engine.mv.sample.scoreRecord.grid.entity.scoreEndDate": "评分结束日期",
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"io.sc.engine.mv.sample.defaultRecord.grid.title": "违约记录列表",
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"io.sc.engine.mv.sample.defaultRecord.grid.entity.customId": "客户标识",
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"io.sc.engine.mv.sample.defaultRecord.grid.entity.defaultConfirmDate": "违约确定日期",
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"io.sc.engine.mv.result.task.progress": "当前正在执行的任务进度:",
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"io.sc.engine.mv.result.grid.title": "验证结果列表",
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"io.sc.engine.mv.result.grid.toolbar.execute": "执行验证",
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"io.sc.engine.mv.result.grid.entity.validateDate": "验证日期",
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"io.sc.engine.mv.result.grid.entity.runtimeParameters": "运行时参数",
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"io.sc.engine.mv.result.grid.entity.runtimeParameters.rateStartDateFrom": "评级开始日期从",
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"io.sc.engine.mv.result.grid.entity.runtimeParameters.rateStartDateTo": "评级开始日期到",
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"io.sc.engine.mv.result.grid.entity.runtimeParameters.performPeriod": "表现期",
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"io.sc.engine.mv.result.grid.entity.runtimeParameters.binomialSignificanceLevel": "二项检验显著水平",
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"io.sc.engine.mv.result.grid.entity.runtimeParameters.chiSquareSignificanceLevel": "卡方检验显著水平",
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"io.sc.engine.mv.result.grid.entity.modelId": "模型标识",
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"io.sc.engine.mv.result.grid.entity.modelName": "模型名称",
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"io.sc.engine.mv.result.grid.entity.executeMode": "执行模式",
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"io.sc.engine.mv.result.grid.entity.totalSampleCount": "总样本数",
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"io.sc.engine.mv.result.grid.entity.defaultSampleCount": "违约样本数",
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"io.sc.engine.mv.result.grid.entity.discrimination": "区分能力",
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"io.sc.engine.mv.result.grid.entity.total": "总体",
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"io.sc.engine.mv.result.grid.entity.total.auc": "AUC(总体)",
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"io.sc.engine.mv.result.grid.entity.total.ar": "AR(总体)",
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"io.sc.engine.mv.result.grid.entity.total.ks": "KS(总体)",
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"io.sc.engine.mv.result.grid.entity.quantitative.auc": "AUC(定量)",
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"io.sc.engine.mv.result.grid.entity.quantitative.ar": "AR(定量)",
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"io.sc.engine.mv.result.grid.entity.quantitative.ks": "KS(定量)",
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"io.sc.engine.mv.result.grid.entity.qualitative.auc": "AUC(定性)",
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"io.sc.engine.mv.result.grid.entity.qualitative.ar": "AR(定性)",
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"io.sc.engine.mv.result.grid.entity.qualitative.ks": "KS(定性)",
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"io.sc.engine.mv.result.grid.entity.auc": "AUC",
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"io.sc.engine.mv.result.grid.entity.ar": "AR",
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"io.sc.engine.mv.result.grid.entity.ks": "KS",
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"io.sc.engine.mv.result.grid.entity.stability": "稳定性",
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"io.sc.engine.mv.result.grid.entity.svd": "SVD",
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"io.sc.engine.mv.result.grid.entity.psi": "PSI",
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"io.sc.engine.mv.result.grid.entity.scaleValidate": "标尺检验",
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"io.sc.engine.mv.result.grid.entity.chiSquare": "卡方检验",
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"io.sc.engine.mv.result.grid.entity.binomial": "二项检验",
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"io.sc.engine.mv.result.curve.references": "参考标准",
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"io.sc.engine.mv.result.curve.viewData": "查看 {type} 数据",
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"io.sc.engine.mv.result.curve.scoreCutOffPoint": "评分截断点",
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"io.sc.engine.mv.result.curve.roc.dd": "(DD)实际违约且预测违约样本总数",
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"io.sc.engine.mv.result.curve.roc.dn": "(DN)实际违约且预测正常样本总数",
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"io.sc.engine.mv.result.curve.roc.nd": "(ND)实际正常且预测违约样本总数",
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"io.sc.engine.mv.result.curve.roc.nn": "(NN)实际正常且预测正常样本总数",
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"io.sc.engine.mv.result.curve.roc.td": "(TD)实际违约样本总数",
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"io.sc.engine.mv.result.curve.roc.tn": "(TN)实际正常样本总数",
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"io.sc.engine.mv.result.curve.roc.x": "(X=ND/TN)违约预测误警率",
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"io.sc.engine.mv.result.curve.roc.y": "(Y=DD/TD)违约预测命中率",
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"io.sc.engine.mv.result.curve.cap.ts": "(TS)评分小于等于截断点的样本个数",
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"io.sc.engine.mv.result.curve.cap.tt": "(TT)样本总数",
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"io.sc.engine.mv.result.curve.cap.tds": "(TDS)评分小于等于截断点的事实违约样本个数",
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"io.sc.engine.mv.result.curve.cap.tdt": "(TDT)事实违约样本总数",
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"io.sc.engine.mv.result.curve.cap.x": "(X)违约样本百分比",
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"io.sc.engine.mv.result.curve.cap.y": "(Y)样本百分比",
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"io.sc.engine.mv.result.curve.ks.n": "(N)评分小于等于截断点事实正常的样本个数",
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"io.sc.engine.mv.result.curve.ks.tn": "(TN)事实正常样本总数",
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"io.sc.engine.mv.result.curve.ks.d": "(D)评分小于等于截断点事实违约样本个数",
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"io.sc.engine.mv.result.curve.ks.td": "(TD)事实违约样本总数",
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"io.sc.engine.mv.result.curve.ks.y1": "(Y1)正常样本占比",
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"io.sc.engine.mv.result.curve.ks.y2": "(Y2)违约样本占比",
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"io.sc.engine.mv.result.curve.psi.scoreSegStart": "分数段开始值(含)",
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"io.sc.engine.mv.result.curve.psi.scoreSegEnd": "分数段结束值(含)",
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"io.sc.engine.mv.result.curve.psi.countDev": "段内个数",
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"io.sc.engine.mv.result.curve.psi.totalCountDev": "总数",
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"io.sc.engine.mv.result.curve.psi.percentDev": "百分比",
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"io.sc.engine.mv.result.curve.psi.countApp": "段内个数",
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"io.sc.engine.mv.result.curve.psi.totalCountApp": "总数",
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"io.sc.engine.mv.result.curve.psi.percentApp": "百分比",
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"io.sc.engine.mv.result.curve.psi.percentDiff": "百分比变化",
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"io.sc.engine.mv.result.curve.psi.percentRate": "百分比相对比例",
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"io.sc.engine.mv.result.curve.psi.weight": "加权系数",
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"io.sc.engine.mv.result.curve.psi.stWeight": "稳定性加权",
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"io.sc.engine.mv.result.chiSquare.grid.title": "卡方检验结果",
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"io.sc.engine.mv.result.chiSquare.level": "评分等级",
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"io.sc.engine.mv.result.chiSquare.pd": "违约概率",
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"io.sc.engine.mv.result.chiSquare.count": "样本总数",
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"io.sc.engine.mv.result.chiSquare.defaultCount": "事实违约样本个数",
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"io.sc.engine.mv.result.chiSquare.chiSquare": "卡方检验值",
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"io.sc.engine.mv.result.binomial.grid.title": "二项检验结果",
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"io.sc.engine.mv.result.binomial.level": "评分等级",
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"io.sc.engine.mv.result.binomial.pd": "违约概率",
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"io.sc.engine.mv.result.binomial.count": "样本总数",
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"io.sc.engine.mv.result.binomial.defaultCount": "事实违约样本个数",
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"io.sc.engine.mv.result.binomial.ndAvg": "正态分布平均数",
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"io.sc.engine.mv.result.binomial.ndSd": "正态分布标准差",
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"io.sc.engine.mv.result.binomial.sl": "显著水平",
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"io.sc.engine.mv.result.binomial.cl": "置信水平",
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"io.sc.engine.mv.result.binomial.zUpper": "正态分布Z值上界",
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"io.sc.engine.mv.result.binomial.zLower": "正态分布Z值下界",
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"io.sc.engine.mv.result.binomial.dUpper": "临界值上界",
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"io.sc.engine.mv.result.binomial.dLower": "临界值下界",
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"io.sc.engine.mv.result.binomial.leUpper": "事实违约个数是否小于等于上界",
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"io.sc.engine.mv.result.binomial.geLower": "事实违约个数是否大于等于下界",
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"io.sc.engine.mv.executorDialog.title": "执行",
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"io.sc.engine.mv.executorDialog.form.entity.rateStartDateFrom": "评级有效期开始日期范围(起始日期)",
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"io.sc.engine.mv.executorDialog.form.entity.rateStartDateTo": "评级有效期开始日期范围(结束日期)",
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"io.sc.engine.mv.executorDialog.form.entity.performPeriod": "评级表现期(月)",
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"io.sc.engine.mv.executorDialog.form.entity.binomialSignificanceLevel": "二项检验采用的显著水平",
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"io.sc.engine.mv.executorDialog.form.entity.chiSquareSignificanceLevel": "卡方检验采用的显著水平",
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"io.sc.engine.mv.executorDialog.form.action.execute": "立即执行"
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}
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