Bank

doi:doi:10.57702/ojij63i4

Bank

Bank dataset from 2014. The dataset contains 41188 records of direct marketing campaigns of a Portuguese banking institution corresponding to each client contacted. We chose 6 numeric attributes (age, duration, euribor of 3 month rate, no. of employees, consumer price index and number of contacts performed during the campaign) as features. We set the number of clusters to K = 10, and impose the target proportions of three groups U = [0.28, 0.61, 0.11] within each cluster.

BibTex:

@dataset{Simiao_Zhang_and_Jitao_Bai_and_Menghong_Guan_and_Yihao_Huang_and_Yueling_Zhang_and_Jun_Sun_and_Geguang_Pu_2024,
    abstract = {Bank dataset from 2014. The dataset contains 41188 records of direct marketing campaigns of a Portuguese banking institution corresponding to each client contacted. We chose 6 numeric attributes (age, duration, euribor of 3 month rate, no. of employees, consumer price index and number of contacts performed during the campaign) as features. We set the number of clusters to K = 10, and impose the target proportions of three groups U = [0.28, 0.61, 0.11] within each cluster.},
    author = {Simiao Zhang and Jitao Bai and Menghong Guan and Yihao Huang and Yueling Zhang and Jun Sun and Geguang Pu},
    doi = {10.57702/ojij63i4},
    institution = {No Organization},
    keyword = {'Bank', 'Bank credit', 'Demographics', 'Fair Clustering', 'Marketing', 'Sensitive Attribute', 'Target Proportions', 'balance', 'default'},
    month = {dec},
    publisher = {TIB},
    title = {Bank},
    url = {https://service.tib.eu/ldmservice/dataset/bank},
    year = {2024}
}