click to zoom| Ditambahkan | August 04, 2020 |
| Kategori | Machine Learning |
| Harga | FREE Deskripsi: Predicting credit card default is a valuable and common use for machine learning. This rich dataset includes demographics, p... |
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Review Dataset Credit Card Default
FREE
Deskripsi:
Predicting credit card default is a valuable and common use for machine learning. This rich dataset includes demographics, payment history, credit, and default data.
Berguna untuk latihan tutorial machine learning, yaitu untuk algoritma prediksi kegagalan/default kartu kredit. Fitur-fitur atau variabel yang ada:
X1: Amount of the given credit (NT dollar): it includes both the individual consumer credit and his/her family (supplementary) credit.
X2: Gender (1 = male; 2 = female).
X3: Education (1 = graduate school; 2 = university; 3 = high school; 4 = others).
X4: Marital status (1 = married; 2 = single; 3 = others).
X5: Age (year).
X6 - X11: History of past payment. We tracked the past monthly payment records (from April to September, 2005) as follows: X6 = the repayment status in September, 2005; X7 = the repayment status in August, 2005; . . .;X11 = the repayment status in April, 2005. The measurement scale for the repayment status is: -1 = pay duly; 1 = payment delay for one month; 2 = payment delay for two months; . . .; 8 = payment delay for eight months; 9 = payment delay for nine months and above.
X12-X17: Amount of bill statement (NT dollar). X12 = amount of bill statement in September, 2005; X13 = amount of bill statement in August, 2005; . . .; X17 = amount of bill statement in April, 2005.
X18-X23: Amount of previous payment (NT dollar). X18 = amount paid in September, 2005; X19 = amount paid in August, 2005; . . .;X23 = amount paid in April, 2005.
Jumlah row: 30.000
Type file: .XLS
Download: Click
