'Young', 'Adult', 'Senior'] df_credit["Age_cat"] = pd.cut(df_credit.Age, interval, labels=cats) df_good = df_credit[df_credit["Risk"] == 'good'] df_bad = df_credit[df_credit["Risk"] == 'bad']
Id 0 Age 0 Sex 0 Job 0 Housing 0 Saving accounts 0 Checking account 0 Credit amount 0 Duration 0 Purpose 0 dtype: int64 # 查看分类特征的唯一值 characteristic = ['Sex','Job','Housing','Saving accounts','Checking account','Purpose'] for i in characteristic: print(f'{i}:') print(da...
编者语: CRM全称是Credit Risk Mitigation,是信用风险缓释工具的意思,即通过风险控制措施来降低借款人未能及时、足额偿还欠款而造成的风险损失或影响程度。本文以漫画的形式介绍了CRM及其它相关概念。敬请阅读。 CRM全称是Credit Risk Mitigation,是信用风险缓释工具的意思,即通过风险控制措施来降低借款人未能及时、足额偿还...
编者语: CRM全称是Credit Risk Mitigation,是信用风险缓释工具的意思,即通过风险控制措施来降低借款人未能及时、足额偿还欠款而造成的风险损失或影响程度。本文以漫画的形式介绍了CRM及其它相关概念。敬请阅读。 CRM全称是Credit Risk Mitigation,是信用风险缓释工具的意思,即通过风险控制措施来降低借款人未能及时、足额偿还...
信用评分:评估风险{% if risk is not none %}信用风险: {{ risk }}{% endif %} 运行应用 最后,我们需要创建一个app.py文件来运行Flask应用。 代码语言:python 代码运行次数:0 运行 AI代码解释 fromappimportappif__name__=='__main__':app.run(debug=True) 总结 在这篇教程中,我们使用Python构建了...
Python Table of Contents I. DETERMINING THE PROBLEMII. EXPLORATORY DATA ANALYSIS (EDA)1. Import dataset and libraries2. Viewing number and types of features in dataset3. Descriptive StatisticsIII. DATA PREPROCESSING1. Data Cleaning2. Data TransformationIV. EVALUATION AND SELECTION OF MODELS1. Featur...
credit_risk = [0 if x=='good' else 1 for x in df_train['credit_risk']] #credit_risk = np.where(df_train['credit_risk'] == 'good',0,1) data = df_train data['credit_risk']=credit_risk 1. 2. 3. 4. 5. 6. 7.
The German Credit Data contains data on 20 variables and the classification whether an applicant is considered a Good or a Bad credit risk for 1000 loan applicants. Here is a link to the German Credit data (right-click and "save as" ). A predictive model developed on this data is expecte...
1.Common variance reduction techniques for Monte-Carlo and application to option pricing (常见蒙特卡罗方差降低方法与期权定价) 2.Importance sampling and change of measure (重点抽样级数和测度变化) 3.Incremental risk charge model and Gaussian Copula for credit risk ...
of multiple actual data set, the average time spent on constructing one model combination per dataset is less than 1 min, which indeed is significantly shorter than the original time required for credit risk assessment and provided a practical tool for the related work of credit risk assessment....