Data
MembershipWoes

MembershipWoes

active ARFF Unknown Visibility: public Uploaded 05-10-2022 by louis geiler
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A certain premium club boasts a large customer membership. The members pay an annual membership fee in return for using the exclusive facilities offered by this club. The fees are customized for every member's personal package. In the last few years, however, the club has been facing an issue with a lot of members cancelling their memberships. The club management plans to address this issue by proactively addressing customer grievances. They, however, do not have enough bandwidth to reach out to the entire customer base individually and are looking to see whether a statistical approach can help them identify customers at risk. The aim is to help them identify these customers.

15 features

MEMBERSHIP_STATUS (target)string2 unique values
0 missing
MEMBERSHIP_NUMBERstring10362 unique values
0 missing
MEMBERSHIP_TERM_YEARSnumeric92 unique values
0 missing
ANNUAL_FEESnumeric3168 unique values
0 missing
MEMBER_MARITAL_STATUSstring4 unique values
2597 missing
MEMBER_GENDERstring2 unique values
611 missing
MEMBER_ANNUAL_INCOMEnumeric798 unique values
1754 missing
MEMBER_OCCUPATION_CDnumeric6 unique values
43 missing
MEMBERSHIP_PACKAGEstring2 unique values
0 missing
MEMBER_AGE_AT_ISSUEnumeric89 unique values
0 missing
ADDITIONAL_MEMBERSnumeric4 unique values
0 missing
PAYMENT_MODEstring5 unique values
0 missing
AGENT_CODEstring4317 unique values
0 missing
START_DATE (YYYYMMDD)numeric1300 unique values
0 missing
END_DATE (YYYYMMDD)numeric1061 unique values
7219 missing

19 properties

10362
Number of instances (rows) of the dataset.
15
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
12224
Number of missing values in the dataset.
8024
Number of instances with at least one value missing.
8
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
77.44
Percentage of instances having missing values.
7.86
Percentage of missing values.
1
Average class difference between consecutive instances.
53.33
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
69.67
Percentage of instances belonging to the most frequent class.
7219
Number of instances belonging to the most frequent class.
30.33
Percentage of instances belonging to the least frequent class.
3143
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

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