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@Matrixzhu 2023-02-27T23:21:56.000000Z 字数 1655 阅读 248

Bank Customer Subscription Product Prediction

Dataset


Background

The topic is based on the forecast of bank product subscription, and we want you to predict whether customers will buy bank products. In the process of communicating with customers, we record the number of times we contacted customers, the duration of the last contact, and the time interval of the last contact. At the same time, we saved the basic information of customers in the banking system, including: age, occupation, marriage , Whether there was a breach of contract before, whether there was a mortgage, etc. In addition, we also counted the current market situation: employment, consumption information, interbank dismantling rate, etc.

Task

To DO: Predict whether the user will purchase the product

field illustrate
age age
job Occupation: admin, unknown, unemployed, management…
marital Marriage: married, divorced, single
education Education level: high school, professional course, university...
default Credit Card Default: yes or no
housing Whether there is a mortgage: yes or no
loan Loan record: yes, no, unknown
contact Contact: unknown, telephone, cellular
month Month of last contact: jan, feb, mar, …
day_of_week Day of the week of last contact: mon, tue, wed, thu, fri
duration Length of last contact (seconds)
campaign Number of times the customer was contacted during the event
pdays The number of days since the last contact with the customer
previous The number of days since the last contact with the customer
poutcome Results of previous campaigns: unknown, other, failure, success
emp_var_rate Employment Change Rate (Quarterly Indicator)
cons_price_index Employment Change Rate (Quarterly Indicator)
cons_conf_index Consumer Confidence Index (Monthly Indicator)
lending_rate3m Interbank Offered Rate 3-Month Rate (Daily Indicator)
nr_employed Number of employees (quarterly indicator)
subscribe Whether the customer made a purchase: yes or no
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