Bank Data Description

The marketing department of a financial firm keeps records on customers, including demographic information and, number of type of accounts. When launching a new product, such as a "Personal Equity Plan" (PEP), a direct mail piece or a targeted email, advertising the product, is sent to existing customers, and a record kept as to whether that customer responded and bought the product. Based on this database of prior cases, the managers decide to use data mining techniques to build customer profile models in order to predict the behavior of future customers.

The data is contained in the file bank_data.csv. Each record is a customer description where the "pep" field indicates whether or not that customer has purchased a PEP. For classification problems, this field is used as the target attribute (with "YES" and "NO") as class labels.

The data contains the following fields

id	a unique identification number (categorical, str)
age	age of customer in years (numeric, int)
income	income of customer (numeric, float)
children	number of children (numeric, int)
gender	MALE / FEMALE
region	INNER_CITY/RURAL/SUBURBAN/TOWN
married	Customer married (YES/NO)
car	Customer owns one or more cars (YES/NO)
save_acct	Customer has a savings account (YES/NO)
current_acct	Customer has a current checking account (YES/NO)
mortgage	Customer have a mortgage (YES/NO)
pep	Customer purchased a PEP, Personal Equity Plan (YES/NO)