数据文件

文档中是购买与不购买产品的银行客户的不同特征，主要包括id号、年龄、职业、婚姻状况、信用卡是否违约、是否有房贷、联系方式、上一次联系的月份、上一次联系的时长、银行同业拆借3个月利率、之前营销活动的结果、在本次营销活动前与客户联系的次数上一次与客户联系后的间隔次数、就业变动率、消费者价格指数、消费者信心指数、雇员人数、客户是否进行购买等等。通过对不同客户的不同特征的相关数据进行分析，包括描述性统计、可视化分析，以及机器学习等等，从而对银行客户购买产品的数据做出专业的分析，并对客户未来购买产品做出预测，得到数据的分析结果。

This dataset documents various characteristics of bank customers who either purchased or did not purchase the bank's product. The covered features include: customer ID, age, occupation, marital status, credit default status, whether the customer holds a mortgage, contact information, month of the last contact, duration of the last contact, 3-month interbank offered rate, outcomes of previous marketing campaigns, number of contacts with the customer prior to the current marketing campaign, interval count since the last contact with the customer, employment variation rate, Consumer Price Index (CPI), Consumer Confidence Index (CCI), number of employees, and whether the customer made a purchase, among others. By analyzing the relevant data of diverse customer characteristics via methods including descriptive statistics, visual analysis, and machine learning, we can conduct professional analysis on the data of bank customers' product purchase behavior, forecast customers' future product purchase intentions, and obtain the final data analysis results.

搜集汇总

背景与挑战

背景概述

该数据集专注于银行客户产品购买预测，包含客户特征（如年龄、职业、婚姻状况）和市场情况数据，旨在通过分析预测客户购买行为。数据文件包括train.csv、test.csv和submission.csv，上传于2023年11月21日。目前平台因维护升级，数据集下载服务暂时不可用。