地球资源数据云——数据资源详情
贷款审批分类数据集
该数据集《Loan Approval Classification Dataset》主要用于二分类任务，数据形态以文本为主，应用场景偏向金融风控。 题目说明：Synthetic Data for binary classification on Loan Approval 任务类型：文本二分类。 建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。 评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。 可用文件：loan_data.csv。 1. Data Source This dataset is a synthetic version inspired by the original Credit Risk dataset on Kaggle and enriched with additional variables based on Financial Risk for Loan Approval data. SMOTENC was used to simulate new data points to enlarge the instances. The dataset is structured for both categorical and continuous features. 2. Metadata The dataset contains 45,000 records and 14 variables, each described below: | Column | Description | Type |
摘要概览
该数据集《Loan Approval Classification Dataset》主要用于二分类任务，数据形态以文本为主，应用场景偏向金融风控。 题目说明：Synthetic Data for binary classification on Loan Approval
任务类型：文本二分类。
建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。
评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。
可用文件：loan_data.csv。
1. Data Source
This dataset is a synthetic version inspired by the original Credit Risk dataset on Kaggle and enriched with additional variables based on Financial Risk for Loan Approval data. SMOTENC was used to simulate new data points to enlarge the instances. The dataset is structured for both categorical and continuous features.
2. Metadata
The dataset contains 45,000 records and 14 variables, each described below:
| Column | Description | Type |