地球资源数据云——数据资源详情
个人开支分析和预算预测
该数据集《Personal Expense Analysis & Budget Prediction》主要用于监督学习任务，数据形态以表格为主，应用场景偏向金融风控。 题目说明：Understanding spending behavior with data visualization and predictive modeling 任务类型：表格监督学习。 建议流程：先做缺失值/异常值处理与特征编码，再比较逻辑回归、随机森林、XGBoost。 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：personal_expense_dataset.csv。 This dataset is synthetically generated using Python to simulate realistic personal expense records. Data generation tools: Python (NumPy & Pandas) Dates, categories, payment modes, and amounts are generated using controlled randomization to maintain realism. No real personal or sensitive information is included. The dataset is 100% safe, anonymous, and open for educational use.
摘要概览
该数据集《Personal Expense Analysis & Budget Prediction》主要用于监督学习任务，数据形态以表格为主，应用场景偏向金融风控。 题目说明：Understanding spending behavior with data visualization and predictive modeling
任务类型：表格监督学习。
建议流程：先做缺失值/异常值处理与特征编码，再比较逻辑回归、随机森林、XGBoost。
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：personal_expense_dataset.csv。
This dataset is synthetically generated using Python to simulate realistic personal expense records.
Data generation tools: Python (NumPy & Pandas)
Dates, categories, payment modes, and amounts are generated using controlled randomization to maintain realism.
No real personal or sensitive information is included.
The dataset is 100% safe, anonymous, and open for educational use.